[fusion_builder_container hundred_percent=”yes” overflow=”visible” flex_column_spacing=”0px” type=”legacy”][fusion_builder_row][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”2″]Research Projects by Subject[/fusion_title][fusion_text]
Note:
Each research project will involve background reading for the interns provided by their mentors.
Each research project will involve a final presentation by the interns.
Interns are expected to work collaboratively on the same project and/or data set.
This may preclude rising seniors from submitting papers based on such projects to the Regeneron Science Talent Search competition
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Applied Artificial Intelligence[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AAI-01 (CSE) | Title: Game Simulation Engine for Evolutionary Game Theory Research Primary Mentor: Golam Md. Muktadir Faculty advisor: Prof. Luca de Alfaro Location: Remote/online Number of Interns: 3Project description: The mentor’s research group is developing a complete game simulation engine for research purposes in the area of Evolutionary Game Theory. In an example scenario, there will be a grid world with different kinds of animals and resources. The engine will simulate evolution of the environment over time and try to find if it can reach a sustainable state. This project is developed in Python and TensorFlow. There are also some AI animals who are weak but can learn to survive! Tasks: The SIP interns’ primary tasks will be to learn Python and add to research ideas. Their secondary tasks will include designing and implement a few animals and running simulations. Designing a good animal is difficult because, if the animal is too strong, the world may collapse, and if it is too weak, it may go extinct! This is also the fun part. Required skills for interns prior to acceptance: Computer programming Skills interns will acquire/hone: Computer programming; game theory; machine learning This research project will allow for remote participation by interns.
|
||||||||||||||||||
| AAI-02 (EPS) | Title: Machine Learning and Mineral Identification on Mars Primary Mentor: Genesis Berlanga Faculty advisor: Prof. Quentin Williams Location: Remote/online Number of Interns: 3Project description: NASA’s Mars rovers take thousands of images and spectra every day. Analyzing this information is a massive task that takes months of work, but with the help of computers, scientists can shorten the time it takes to arrive at exciting results. In order to train a computer to be a geological assistant, the SIP interns will program a computer to automatically identify rocks and minerals found on the surface of the Moon and Mars. The interns will help build neural networks modeled after the circuitry of brain neurons to train the computer to accomplish this task using rocks we find on Earth. This research project will inform future research for Mars rovers like Curiosity or the upcoming Perseverance, by finding ways to simplify rock and mineral identification while roving the surface of another planet. Tasks: The SIP interns’ tasks will include: (1) identifying spectra and images of rocks and minerals relevant to the Moon and Mars; (2) programming in Python, MATLAB, or R; and (3) building a neural network that automatically identifies minerals. Computer programming experience is encouraged but not necessary. The mentor will provide training. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Anthropology[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ANT-01 | Title: Technology and Oral Story Collection of Indian Immigrants in the USA Primary Mentor: Dr. Annapurna Pandey Secondary Mentor: Kati Greaney Location: Remote/online Number of Interns: 4Project description: These days, one often hears that we human beings are primarily story tellers. We tell stories about ourselves as well as about others. What these stories tell us is the rich experience human beings have acquired in their life. The world in which we live today is largely created by technology. The mentor and SIP interns will use various tools provided by technology in their digital story telling research. This project will encourage SIP interns to collect stories about the immigrant experience in the United States. For the last three decades the mentor has been working on the Indian diaspora in the Greater Bay Area, California. The mentor has made two films, “Homeland in the Heart” and “Life Giving Ceremony of Jagannath” documenting the involvement of Odia people (people from the state of Odisha) in building a community and developing a sense of belonging to the United States. The mentor would like to broaden the scope of this research by incorporating the experiences of other Indian immigrants. Tasks: This project will give an opportunity to the SIP interns to collect oral history material about the experiences of immigrant parents, grandparents, and their American-born children. The material will include streaming audio and written transcripts accessible online in digital formats. The mentor and SIP interns will use various available technology tools. The mentor’s aim in this project is to collect interviews of Indian immigrants in the USA. The SIP interns will interview various members of the Indian community and collect their experiences in this country compared to their experience in their homeland that they have left behind. These interviews are a unique source of contemporary history through the experiences of the immigrants. Past studies have shown that this kind of research has revealing consequences for both the researchers as well as the subjects of their research. [/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Astronomy & Astrophysics[/fusion_title][fusion_text]
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Biomolecular Engineering[/fusion_title][fusion_text]
[/fusion_text][fusion_separator top=”50″ /][fusion_text]
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-02 | Title: SpokeIt: Preparing a Speech Therapy Game for Global Delivery Primary mentor: Jared Duval Faculty advisor: Prof. Sri Kurniawan Location: Remote/online Number of interns: 6Project description: Therapy is costly, time-consuming, repetitive, and difficult. Games have the power to teach transferable skills, can turn repetitive tasks into engaging mechanics, have been proven to be effective at delivering various forms of therapy, and can be deployed at large scales. Games move us. The SIP interns will work to bring our speech therapy game, SpokeIt, into the world. SpokeIt (http://SpokeIttheGame.com) is a speech therapy game for children born with orofacial cleft. It has been in development for four years, has been studied clinically, and features cutting edge tools that can critically listen to speech. SpokeItTheGame has recently partnered with SmileTrain — an organization that has supported over 1.5 million free cleft surgeries — and is gearing up to be deployed around the world (it is nearly ready for launch on the App Store)! The SIP interns will primarily be working on translating SpokeIt for release on Google Play as well as working towards supporting new languages. Tasks: Depending on the SIP interns’ expertise and interests, there are many opportunities to work on the research project. All interns will be expected to work on polishing existing game content or creating new content as well as analyzing user studies and playtests. Some example tasks include working on animations, sprite sheets, game engine components, art assets, databases, and analyzing user study data. For development, the mentor’s research group works primarily in Xcode, Unity, and Android Studio. The group uses various Adobe applications for design work, such as Illustrator, XD, Photoshop, After Effects, and Character Animator. The SIP interns will work towards translating SpokeIt to work on Android devices and towards adding support for new languages. The interns will need to have ; access to the Adobe Creative Cloud, an Android device, and an Apple computer. Required skills for interns prior to acceptance: Computer programming (proficient) Skills interns will acquire/hone: Computer programming; statistical data analysis; field work URL: http://SpokeIttheGame.com This research project will allow for remote participation by interns. |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-04 | Title: Rumors Primary mentor: Julin Song Faculty advisor: Prof. Jim Whitehead Location: Remote/online Number of interns: 3Project description: The goal of this research project is to investigate the generative power of cascading rumors in simulating a world with a rich history. The research question is to investigate the potential for emergence using cascading errors (differing from cascading changes in that errors/rumors would be corrected when they are recognized as errors, say if the new story spreads back to the original source). Concrete deliverables will include a game with the simulation engine running, giving players the option to intervene in the world by manually injecting events, or view the networks of cascading rumors from different perspectives. Tasks: The SIP interns’ tasks will include: (1) specific, bite-sized programming tasks with lots of detail (involving user interface and internal logic); and (2) authoring of content in the form of simple stories like “somebody’s chicken laid a blue egg” with a subject, event/action, possible object, and some descriptor like color or number, as well as authoring the possible values for names, object types, actions and descriptors (which will serve as seeds for procedural content generation). If the interns and mentor make enough progress for a paper submission, interns will also be involved in processes of paper-writing and literature review. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming This research project will allow for remote participation by interns.
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-05 | Title: Towards Immersive Media for Emotionally Intelligent Virtual Reality Experiences Primary mentor: Aviv Elor Faculty advisor: Prof. Sri Kurniawan Location: Remote/online Number of interns: 3Project description: Immersive Virtual Reality games are powerful mediums to help make task-based rehabilitation more accessible, affordable, and accurate. Subsequently, emotion and self-perception are crucial elements of mental health but are not often explored or monitored in the modern healthcare context. How could a virtual world be personalized if we understand how users feel as they undergo rehabilitation? What if the very world the user performs their rehabilitation in becomes transformed around them – to help motivate and adapt to the difficulty of therapeutic tasks based on each individual’s emotional state? With recent advances in immersive virtual reality and affective computing, this research project will explore the development of a virtual world to accomplish such through utilizing commercially available Virtual Reality systems, haptic feedback vests, olfactory masks, biofeedback sensors, and the Unity Game Engine. Tasks: The SIP interns will work together to collaboratively solve complex design problems towards creating interactive playable prototypes using Unity. The interns will prototype engaging experiences that incorporate runtime data communication, adaptive game engine content, and immersive media 3DUI interaction as well as collect user feedback to iteratively improve and support the design process. The interns will communicate with engineers and partner researchers during implementation and coordinate development efforts. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis; field work; game development URL: https://www.avivelor.com/blog This research project will allow for remote participation by interns.
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-06 | Title: Design and Development of a Social Wearables Kit for Use in Educational Live Action Role Play Primary mentor: James Fey Faculty advisor: Prof. Katherine Isbister Other mentor: Devi Acharya Location: Remote/online Number of interns: 3Project description: Using a design-based research approach, we propose to design, develop, and repeatedly deploy a kit of hardware and activities that targets the issue of creating coding communities with a novel combination of instruction and technology–the use of edu-LARP (a structured, live-action roleplay experience that teaches through social enactment and reflection) as the primary mode of engagement, and a focus on computational interest-building through the creation of social wearable devices aimed at augmenting the campers’ interactions during the camp experience. Both of these strategies place the emphasis on social interaction during the learning, and the solving of socially-relevant technical challenges. Tasks: The SIP interns will: (1) design and test social wearable technology; (2) iterate on existing maker kits to improve their use; (3) explore new and interesting ways of fabricating hardware; (4) create games and activities with these social wearables; and (5) identify how the creation of social wearables can improve interest in computational communities of making. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; field work; human computer interaction design techniques URL: https://setlab.ucsc.edu/ Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-08 | Title: Automatic Playtesting for Game Boy Games Primary mentor: Isaac Karth Faculty advisor: Prof. Adam M. Smith Other mentor: Prof. Nathan Altice Location: Remote/online Number of interns: 3Project description: The SIP interns will contribute to the development and evaluation of a Game Boy game playtesting tool. The interns will work with both commercial Game Boy games and those produced by a game generator (from another SIP research project). Using the mentor’s lab’s existing machine playtesting tools (via programming and recording of human gameplay samples), the mentor and interns will use AI to try to discover the interesting moments and summarize them in visual playtest reports. Working in collaboration with an expert on the Game Boy platform, the mentor and interns plan to run the games on the original Nintendo hardware. This research project will contribute to the fields of software testing, generative design, game design, and code generation. Tasks: The SIP interns will do some or all of the following: (1) setup an automated playtesting software environment; (2) collect games to test; (3) record human gameplay for reference; (4) run machine playtesting experiments; (5) automate the analysis of experimental data; (6) automate the format of playtesting reports; and (7) coordinate with the game generation team on how to auto-test each generated game. Programming for this research project will use Python and Javascript. Interns can contribute to the project without programming, but prior experience with some kind of programming would be helpful. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming URL: https://designreasoning.soe.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-09 | Title: Automatic Generation of Game Boy Games Primary mentor: Tamara Duplantis Faculty advisor: Prof. Nathan Altice Other mentor: Prof. Adam M. Smith Location: Remote/online Number of interns: 2Project description: The SIP interns will contribute to the design and development of a generator that will make playable games for the Game Boy platform. Guided by an expert on developing for the Game Boy platform, the interns will work on generating the ROMs via a variety of machine learning and constructive procedural generation techniques (via programming and artistic asset creation). Working in collaboration with another SIP team, the mentor and interns will evaluate the results and implement them on original Game Boy hardware. Work on this research project will contribute to the fields of software testing, generative design, game design, and platform studies. Development will take place in Python, JavaScript, and potentially C. The mentors will teach the programming languages as necessary, but prior experience with some kind of programming is recommended. Tasks: The SIP interns will be asked to: (1) setup game generation software environments; (2) collect and play relevant games for inspiration; (3) brainstorm approaches to game generation; (4) implement at least two approaches to game generation, one focused on automatically remixing existing games, and one focused on assembling authored components into a cohesive whole; (5) analyze and interpret the generated games; and (6) coordinate with the Automatic Playtesting team on how to auto-test each generated game. Required skills for interns prior to acceptance: Computer programming Skills interns will acquire/hone: Computer programming URL: https://designreasoning.soe.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-10 | Title: Game-Making Tools Survey Primary mentor: Jared Pettitt Faculty advisor: Prof. Nathan Altice Other mentor: Celeste Clark Jewett Location: Remote/online Number of interns: 2Project description: There are many different tools used to produce different kinds of video games, from casual tools like Twine, to professional tools like Unity 3D. These tools have, built into their design, certain affordances or expectations that shape what people tend to make using them. The mentor is working on research regarding game-making software, and this research project is a survey of different game-making tools, by using the tools to produce small games and then evaluating them afterwards. If the SIP interns are interested in making games, either in learning how to use high-level software, or just want to learn how to do it because it seems fun (it is), then they will definitely find this research project interesting to work on! Tasks: The SIP mentor and interns will be using several design game creation tools to make small games over the course of the summer, while evaluating how using the tool feels and how its design affects what they make using it. There are many tools that do not require any kind of programming or video game knowledge at all, so if the interns are at all interested but feel that you may not know enough to be helpful, they should not worry about that! The SIP interns will be learning, making games with, and evaluating several of the following tools, depending on their programming skill level: Twine, Bitsy, Pico-8, Unity 3D, Unreal Engine, and GameMaker. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| CPM-12 | Title: American Indian Art Web Application Primary mentor: Sarah Frost Faculty advisor: Prof. Angus Forbes Other mentor: James Fey Location: Remote/online Number of interns: 3Project description: The SIP mentor and interns will build an interactive web application with the goal of teaching high-school aged students about historic and current American Indian art and artists. The group will develop the HTML, CSS, and JavaScript for the website, and compile relevant content about historical and current American Indian artists for the website. The SIP interns will learn about front-end and back-end web development, creating educational content, transferring files from personal computers to servers, and best practices for presenting information to users. The website will be hosted on Amazon Web Services and it will be made available to the public. Tasks: The SIP interns’ tasks will be modified based on their interests, but can include: (1) development of an interactive web application using JavaScript and Py4Web framework; (2) research to identify notable historical and current American Indian artists; (3) front end web design using HTML and CSS; (4) user interface (UI) design, building wire frames, and conducting usability interviews; (5) development of curriculum modules for use in high schools to convey information about American Indian artists; and (6) hosting a website on Amazon Web Services and setting up a custom domain name. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming URL: http://www.sarahfrost.org This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Computer Science/Computer Engineering[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CSE-01 | Title: Rip Current Detection: A Machine Learning Approach Primary mentor: Akila De Silva Faculty advisor: Prof. Alex Pang Location: Remote/online Number of interns: 3Project description: Rip currents are the main beach hazard affecting beachgoers who could even face death as a result. The mentor is currently working on building an application, using artificial intelligence (AI) and machine learning (ML), that could easily detect and visualize potentially hazardous rip currents. This summer, the mentor and SIP interns will use ML and AI techniques to classify coastal images as rip current or non-rip current images. Furthermore, during this classification process, the SIP interns will visualize what unique features could be used to identify images of rip currents from non-rip currents. Finally, if time permits, the SIP interns will gain exposure to detection and localization of rip currents in a coastal image. Tasks: The SIP interns will: (1) learn to use Python for programming; (2) gain exposure to machine learning frameworks such as TensorFlow and Keras; (3) gain exposure on how to collect data from online resources; (4) gain exposure to multiple ML/AI techniques for image classification; (5) gain exposure to detect and localize objects in an image (if time permits); (6) learn how to critically read reserach papers; and (7) learn how to be effective in a team research environment. Required skills for interns prior to acceptance: Computer programming; statistical data analysis Skills interns will acquire/hone: Computer programming; statistical data analysis URL: http://users.soe.ucsc.edu/~audesilv/ Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-02 | Title: Fluid Flow Pattern Analysis and Visualization Primary mentor: Fahim Hasan Khan Faculty advisor: Prof. Alex Pang Location: Remote/online Number of interns: 3Project description: Flow visualization (FlowVis) is a subfield of scientific visualization and closely associated with computer graphics. Most fluids (gases and liquids such as air, water, etc.) are transparent, and their flow patterns are invisible to the human eyes without methods to make them visible. Flow visualization is the process of making the physics of fluid flow directly accessible to visual perception by making the flow patterns visible to get qualitative or quantitative information on them. These flow visualizations are often rendered using the same 2D and 3D computer graphics pipelines used for movies, games, and related applications thus making them closely associated with computer graphics. The mentor’s research group works in the field of scientific visualization and computer graphics. One of his research focus involves the challenges of analyzing and visualizing time-varying 3D flow in an efficient manner for various real-life applications. One of the critical tasks in flow analysis and visualization is optimally utilizing the graphics processing unit (GPU) of computational devices. The GPU plays two different crucial roles in this process, (1) using GPGPU (General-purpose computing on graphics processing units) for faster processing of huge amount of flow data, and, (2) rendering the high-quality 3D graphics for visualizing the flow. This research group is currently working towards the goal of developing an iPhone/Android app to analyze and visualize rip current patterns from live video of a cellphone camera in a superimposed fashion. This app will render the visual information of the flow pattern directly on the live video, effectively converting mobile devices to visual analysis tools to be used by surfers and swimmers in real life. Tasks: The SIP interns will be involved in a research project for superimposed visualization of flow pattern analysis. They will learn basic programming using Python and/or C++, do literature reviews on a topic and read related research papers, and work on an academic research project. The interns will practice extensive and effective use of Google and other online tools to solve programming problems. The SIP interns will have exposure to a few visualization software tools, the 3D graphics development pipeline for developing visualization applications, and the use of GPU for both computations (GPGPU) and rendering (3D graphics). Depending on their level of expertise, the interns will participate in the development of the iPhone/Android app for rip current visualization. If time permits, the interns will have exposure to some machine learning techniques for pattern analysis of flow data. Some previous experience with programming is preferred, but not required. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis URL: https://www.soe.ucsc.edu/people/fkhan4 Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-04 | Title: Exploring Distributed Learning Paradigms Primary mentor: Harikrishna Kuttivelil Faculty advisor: Prof. Katia Obraczka Location: Remote/online Number of interns: 3Project description: Machine learning is a field that is proliferating and drawing in high interest and investment as it continues to diversify to meet the demands of its various applications. Recently, factors including privacy concerns, increasing prevalence and computational ability of personal devices, the proliferation of IoT devices, and the general trend of decentralization in technology have led to the increased research and development of distributed learning paradigms. This research project applies networking principles to validate the principles of federated learning and extend it into decentralized learning approaches while using real, low-cost devices to form a network and collectively gather data and learn from all nodes within the system. Tasks: The SIP interns will first learn about the basics of machine learning and implementing machine learning algorithms within Google’s TensorFlow platform. Then interns will assist the mentor in configuring Raspberry Pi devices for TensorFlow, and then assess the performance of these devices in handling basic machine learning tasks. The interns will then learn about the basics of distributed machine learning. They will help organize multiple Raspberry Pi devices into a network and support the mentor to develop communication protocols efficient for the intended application. Finally, the interns will get a chance to experiment with different variations of distributed learning by implementing such schemes on the Raspberry Pi network and analyzing the results of the experiments. Throughout the process, the SIP interns will also aid the mentor in collecting, labeling, and processing data to use for the tests. The interns will gain skills in research, programming, applying machine learning, distributed systems, networking, and data processing. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-05 | Title: Data Prefetching in Hardware Primary mentor: Peter Braun Faculty advisor: Prof. Heiner Litz Location: Remote/online Number of interns: 2Project description: As CPUs become faster and more powerful, the memory becomes a greater bottleneck in the traditional von Neumann computer architecture. If a program requires some data that is not already in cache, it must wait 100x longer to receive it than the time it takes to access cached data. This can lead to a significant increase in program runtime. One approach to this problem is data prefetching. A prefetching algorithm generally observes the sequence of memory accesses and predicts what memory address will be needed in the near future, prefetching it to cache. Current prefetching algorithms do not perform well on certain important classes of applications. This motivates the study of why these algorithms perform poorly. Are there patterns within the memory access stream that are not currently understood and exploited? Can one develop a general prefetching algorithm, perhaps leveraging recent advances in machine learning? Tasks: The SIP interns will collect instruction traces for a variety of applications. The interns will compare characteristics of the trace with the full application and determine which subsection of the full trace is representative of the full program using a microarchitectural simulator. This will include adapting scripts written in Bash/Python, using the Linux command line, and learning fundamental computer architecture principles. Required skills for interns prior to acceptance: Computer programming; Linux Skills interns will acquire/hone: Computer programming; Linux; Bash scripting; Python; computer architecture URL: https://people.ucsc.edu/~hlitz/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-06 | Title: Neural Data-toText Generation Primary mentor: Rongwen Zhao Faculty advisor: Prof. Alex Pang Location: Remote/online Number of interns: 3Project description: Data-to-text is one of the key tasks in natural language generation. It aims to generate meaningful and fluent natural language text from non-linguistic input data. In this research project, given a set of ⟨ Subject, Predicate, Object ⟩ RDF triples, the SIP mentor and interns will try to build a system which can generate a single sentence or a sequence of sentences describing these triplets explicitly. Traditionally, most approaches that have been designed are rule-based and too complex in general. Recently, neural methods based on deep learning (DL) have produced state-of-the-art performance in natural language generation. The SIP mentor and interns will build a neural network utilizing different latest language models. Finally, the system will be tested on benchmark datasets with the goal of outperforming other models. Tasks: The SIP interns will: (1) learn how to use Python for programming; (2) gain experience in dealing with large text datasets; (3) gain exposure to popular deep learning frameworks, e.g., PyTorch; (4) gain exposure to the latest language models for natural language generation; (5) learn how to build and train a neural network for text generation; (6) learn how to read related research papers; and, most importantly, (7) work collaboratively as a team. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis URL: https://webnlg-challenge.loria.fr Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-07 | Title: Neural Style Transfer (Transferring Style from Famous Paintings) Primary mentor: Saeed Kargar Faculty advisor: Prof. Faisal Nawab Location: Remote/online Number of interns: 4Project description: One of the biggest developments in deep-learning-driven image modification is Neural Style Transfer (NST), introduced by Leon Gatys et al. (2015). NST refers to a class of software algorithms that manipulate digital images or videos to adopt the appearance or visual style of another image. NST algorithms are characterized by their use of deep neural networks in order to perform the image transformation. Common uses for NST are the creation of artificial artwork from photographs, for example by transferring the appearance of famous paintings to user supplied photographs. Several notable mobile apps use NST techniques for this purpose, including DeepArt and Prisma. This summer, the mentor’s research group will apply an advanced machine learning technique to adapt the appearance or visual style of one image to another. The SIP interns will learn various deep learning concepts and tools — e.g., using the Keras library, pre-trained models such as the VGG19 network, and popular online tools such as Google Colab to solve programming problems. The mentor will work with the interns to implement an advanced technique of a research paper from scratch. The SIP interns will learn how to read a research paper and implement it, and will learn one of the most advanced concepts in deep learning territory. Finally, if time permits, the SIP interns will gain exposure to applying NST on video datasets too. Tasks: The SIP interns will gain exposure to: (1) Python programming; (2) machine learning frameworks such as TensorFlow and Keras; (3) data collection from online resources; (4) one of the most recent and advanced concepts in deep learning; (5) application of NST to image datasets (6) application of NST to video datasets (if time permits); (7) critical reading of research papers; and (8) collaborating effectively in a team research environment. Required skills for interns prior to acceptance: Computer programming (familiarity with Python and Google colab) Skills interns will acquire/hone: Computer programming in Python; machine learning and deep learning Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-08 | Title: Question Answering Data Collection and Analysis Primary mentor: Geetanjali Rakshit Faculty advisor: Prof. Jeffrey Flanigan Location: Remote/online Number of interns: 3Project description: Natural language processing is about making computers learn language. It encompasses a lot of exciting problems like algorithms to teach a computer to translate input from one language to another, for example, English to French (machine translation), have a computer predict if a restaurant review written by someone is positive or negative (sentiment analysis), and so on. The goal of this research project is to build automated question answering systems/models that have a deeper understanding of the text in which to look for answers to the question asked by a user, similar to how humans might do it in a reading comprehension task. To this end, the mentor’s research group collects good-quality crowdsourced data, and investigates the quality and suitability of the data for use in building question answering models that are more interpretable. Tasks: The SIP interns working on this research project may help with collecting crowdsourced data from question answering/reading comprehension tasks. The main focus will be on analyzing these data, and creating automated tests to check the quality of data that are collected using crowdsourcing and their suitability for use in the question answering problem at hand. The interns will learn to program in Python, work with real world datasets, understand relevant concepts from natural language processing, and see these concepts in action. Based on the level of interest and preparedness of the interns, the mentor and interns may also do some statistical analysis of the data, to extract recurring patterns and cues helpful for finding answers, and possibly some machine learning/deep learning. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis URL: http://users.soe.ucsc.edu/~geet This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-09 | Title: Origami Robot: Modeling and Simulation Primary mentor: Samira Zare Faculty advisor: Prof. Mircea Teodorescu Location: Remote/online Number of interns: 3Project description: Origami is a newly emerging field in robotics that can help when limited space is available. They have many applications, from solar panels to medical devices. These deployable structures are able to move and change their shapes and structures based on their environment. For instance, solar origami panels can become compact to transfer and then deploy to their final structure. The mentor’s research group designs, models, and develops a dynamical simulation in Autodesk Inventor and uses MATLAB to analyze and understand their movements. Tasks: The SIP interns’ primary tasks will be learning Autodesk Inventor and MATLAB. Their secondary tasks will be to come up with Origami design ideas and apply a dynamical simulation to understand them. Finding an origami design that can be applied to real-world problems could be challenging. They can be too complex to control and model or too simple to perform any movement. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming (MATLAB, Python); statistical data analysis; 3D modeling; simulation This research project will allow for remote participation by interns.
|
||||||||||||||||||
| CSE-10 | Title: Game Engine Based Simulation for Autonomous Vehicles Primary mentor: Abdul Jawad Faculty advisor: Prof. Jim Whitehead Location: Remote/online Number of interns: 3Project description: Rigorous testing is mandatory for autonomous vehicles to make them safe before we employ them in the real world. The goal of this research project is to use simulation technology in testing autonomous vehicles (creating realistic 3D environments and naturalistic non-player character behavior from other cars). Specifically, the mentor’s resaerch group uses Unreal Engine (widely used game engine) and Behavior Tree (widely used in AAA games) for simulating naturalistic car behavior. This research project is developed in C++. Tasks: The SIP interns’ task will include: (1) learning how to code in C++ in Unreal Engine; and (2) making a user interface for the designer to use the behavior tree tool. Overall, the interns will learn to work with Unreal Engine, build a plugin for the engine, and gain exposure to collaborative research work. They will also learn how to effectively search into the documentation. Finally, the SIP interns will gain exposure to the current research effort on autonomous vehicles. Required skills for interns prior to acceptance: Computer programming Skills interns will acquire/hone: Computer programming; UI design URL: https://github.com/AugmentedDesignLab/CarBehaviorTree This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Ecology & Evolutionary Biology[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| EEB-01 | Title: Mechanisms for Kelp Forest Resiliency Primary mentor: Joshua Smith Faculty advisor: Prof. Mark Carr Location: Remote/online Number of interns: 4Project description: In kelp forests along the central coast of California, active sea urchin grazing has shifted a once continuous kelp forest landscape to underwater ‘sea urchin barrens’ that are void of kelp and associated species. The mentor’s current research focuses on the processes responsible for these shifts from forested to barrens states and the recovery (i.e., resilience) of the forested ecosystem. The mentor’s research group explores sea urchin grazing behavior that has led to widespread kelp forest loss and how factors such as predators, disease, and disturbance might contribute to sea urchin population control and the recovery of kelp forest ecosystems. Tasks: The primary remote responsibility for SIP interns is three-fold: (1) improve the design of a machine-learning based program to quantify consumed algae particles in sea urchin diets (basic knowledge of a computer programming language such as Python, Java, and/or R is preferred); (2) conduct data analyses on long-term datasets collected through subtidal surveys; and (3) analyze high-resolution photo quadrats collected from subtidal surveys. The interns will be responsible for collecting data on the presence of invertebrates and algae from photo plots. Overall, the interns will gain skills and experience in: field research, laboratory safety and training, experimental design, and in applying novel technology to solving ecological problems. The final SIP product will hopefully culminate in a peer reviewed publication in a scientific journal. Required skills for interns prior to acceptance: Computer programming (strongly emphasized) Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis; field work; application of novel technologies to solving ecological problems (e.g., machine learning, particle recognition) URL: http://www.joshuagsmith.com This research project will allow for remote participation by interns.
|
||||||||||||||||||
| EEB-02 | Title: Heating Up the Battle of the Sexes: Temperature Effects on Reproductive Behavior Primary mentor: Doriane Weiler Faculty advisor: Prof. Suzanne Alonzo Location: Remote/online Number of interns: 3Project description: Rising global temperatures are one of many pervasive effects of anthropogenic climate change. Temperature shapes the rate of biochemical processes and has strong impacts on animal physiology and behavior. However, little research has been dedicated to understanding how chronic warming impacts reproductive behavior. This project uses western mosquitofish (Gambusia affinis) as a model system to explore how temperature shapes the evolution of male-female interactions. Mosquitofish are an invasive species of freshwater fish that have been widely introduced to consume mosquito larvae. Their mating system is characterized by persistent male mating attempts – males spend 70%–90% of their time pursuing females! While this behavior benefits males by increasing their reproductive success, it can be very costly for females, which can evolve special traits to avoid males, such as greater swimming speeds. Temperature may intensify or weaken this evolutionary “battle of the sexes,” depending on how it impacts both male and female behavior. To understand how temperature impacts mosquitofish reproductive behavior, SIP interns will help analyze behavior videos of mosquitofish from populations across a broad thermal gradient. This research project will provide students with a strong background in animal behavior experimental design and analysis. Tasks: The SIP interns will primarily assist with: (1) analyzing behavior videos to record male and female mosquitofish behavior at different temperatures, and (2) analyzing fish photographs using ImageJ software to measure morphological traits such as body length and pigmentation. Over the course of this project, the SIP interns will gain an integrative perspective on studying animal behavior and will have a genuine experience working on many aspects of behavioral research, from experimental design to data analysis. This research project is an ideal fit for interns who are interested in animal behavior, fish, aquatic science, and/or ecology. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis; field work URL: https://doriweiler.wordpress.com/, https://alonzo.sites.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| EEB-03 | Title: Hawksbill Sea Turtle Ecology and Conservation in the Gulf of California, Mexico Primary mentor: Luli Martinez Estevez Faculty advisor: Prof. Don A. Croll Location: Remote/online Number of interns: 3Project description: Hawksbill sea turtles are critically endangered worldwide. The Eastern Pacific population, which distributes between Mexico and Ecuador, is the most threatened hawksbill population. Unlike other global hawksbill populations that tend to forage on coral reefs, Eastern Pacific hawksbill turtles use mangrove estuaries for foraging and nesting. These habitats are also crucial for small scale fisheries in the Gulf of California, Mexico. By using different methods (i.e., acoustic and satellite telemetry, cameras, and habitat transects), this research project seeks to understand which habitats hawksbills use in the Gulf of California, how they use them, and how these habitats can be protected effectively. Tasks: This research project will give the SIP interns the opportunity to learn about conservation science and sea turtle research. The interns’ work will be entirely computer-based so bringing a laptop is highly encouraged. The interns will work on two main aspects: (1) analyzing underwater photographs to determine the abundance of the most important food items for the species; and (2) collect information on the spatial conservation strategies that are contributing to the protection of the species. The interns will learn how to do an efficient web search and how to build/analyze a database with the information. In a broader sense, the interns will learn the basic concepts of Conservation Biology and sea turtle biology. They will also get a sense of the work behind field science. Required skills for interns prior to acceptance: Spanish reading proficiency (preferred, if possible – not required) Skills interns will acquire/hone: Statistical data analysis; efficient web search URL: https://ccal.ucsc.edu/ Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| EEB-04 | Title: Abalone Habitat Associations Primary mentor: Taylor White Faculty advisor: Prof. Pete Raimondi Location: Remote/online Number of interns: 3Project description: In Southeast Alaska, pinto abalone (Haliotis kamtschatkana) are listed as a “Species of Concern” under the Endangered Species Act, yet little is known about habitat types that promote large abalone populations, individual abalone growth rates, and recruitment of young of the year. These associations likely differ across Alaska, where there are different densities of sea otters. Sea otters have a substantial effect on their environment. By voraciously consuming herbivores like sea urchins and even abalone, otters indirectly promote algal species and therefore change available habitat. The focus of this research project is to determine abalone habitat associations and shifts in these relationships across Southeast Alaska. Tasks: The goal of this research project is to understand drivers of dense abalone populations and to identify specific habitat and substrate types that promote population growth. To determine these relationships, SCUBA divers collected photos along underwater transects at sites across Southeastern Alaska. The SIP interns will learn how to identify algae species in these photos. Then, using ImageJ software, the interns will record algae and substrate percent cover. Finally, using JMP Pro, the interns will determine novel correlations between previously collected data on abalone densities to habitat type and abundance. Additional comparisons may include urchin biomass and sea otter presence in relation to habitat. These associations are important for the management of abalone in Alaska. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Statistical data analysis; marine species identification URL: https://rclab.ucsc.edu/home This research project will allow for remote participation by interns.
|
||||||||||||||||||
| EEB-05 | Title: Is Quicker Sneak-Spawning a Benefit of Helping a Reproductive Competitor? Primary mentor: Matthew Kustra Faculty advisor: Prof. Suzanne Alonzo Location: Remote/online Number of interns: 2Project description: Alternative reproductive tactics are observed in many species, often as two distinct male types, a territory holding male and a sneaker male that sneaks mating opportunities from the territory holding male. Although the maintenance of these two discrete tactics has been a major focus of research, we have little understanding of the evolution and maintenance of more than two tactics. The ocellated wrasse (Symphodus ocellatus), a Mediterranean fish species, has three alternative male reproductive tactics. Nesting males make nests, chase away sneakers, court females, and provide all parental care. Sneaker males try to join nesting males and females during mating events. Satellite males help the nesting male by chasing away sneakers but will also compete with them by joining mating events between the nesting male and females. The mentor’s research group is investigating the benefits of being a satellite male that may help maintain this third alternative reproductive tactic. In this research project, the SIP mentor and interns will analyze behavior videos to see if satellite males are able to join spawning’s between nesting males and females faster than sneaker males. Tasks: The SIP interns will primarily be analyzing underwater videos of fish mating behavior by recording the time it takes for sneaker and satellite males to reach and spawn at a nest. While collecting the data from these videos, the interns will learn how to properly manage collaborative data sets. Towards the end of the summer, the SIP interns will learn how to perform basic statistical analyses and make graphs in the R programming language. Additionally, the interns will learn more about behavior and evolution through paper discussions to put this research experience in the broader context of evolution and behavioral ecology. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis URL: https://mattkustra.wordpress.com/, https://alonzo.sites.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| EEB-06 | Title: Comparing Convergence, Biases, and Data Gaps in Carnivorous Marine Mammal Feeding Strategies Primary mentor: Jezebel Powers Faculty advisor: Prof. Rita Mehta Other mentor: Dr. Sarah Kienle Location: Remote/online Number of interns: 2Project description: Carnivorous marine mammals (e.g., cetaceans, pinnipeds, polar bears, and sea otters) play important roles as top predators in marine ecosystems worldwide. However, these animals can be challenging to study due to their large body size, remote and often inaccessible habitats, and lack of representation in animal care facilities. Therefore, data on the foraging ecology and behaviors of many species are lacking and/or poorly understood. One of the major research interests of the mentors is characterizing and comparing foraging strategies of carnivorous marine mammals. These data are critical for understanding the role different variables play in shaping marine mammal feeding strategies and how these animals will (and are) responding to widespread environmental changes. The goal of the SIP project is to synthesize current knowledge of marine mammal foraging ecology and behavior, as well as highlight existing biases in available data and propose areas of research that are needed to better understand the feeding biology of these marine predators as they cope with a rapidly changing environment. Tasks: The SIP interns working on this research project will have three main responsibilities: (1) performing systematic literature searches on carnivorous marine mammal feeding biology, including behavior, performance, habitat use, and morphology, (2) conducting systematic image and video searches of opportunistically collected observations of wild feeding behavior, and (3) analyzing feeding images and video data to obtain quantitative data on marine mammal foraging ecology and behavior. The interns will gain extensive experience in the scientific process, from gathering background information, reading and evaluating the scientific literature, conducting data and statistical analyses, and presenting scientific research to the scientific community and general public. The research from this project will be incorporated into a scientific manuscript that will be submitted to a peer reviewed journal for publication. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Statistical data analysis; literature searching, reading, and interpreting scientific articles; data entry; photo and video data analysis; scientific writing; creating scientific illustrations, figures, and tables URL: https://sarahskienle.wordpress.com/ This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Electrical Engineering[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ELE-01 | Title: Electro Plasmonic Nanoelectrode: Label Free Neurophotonics for Ultrahigh Bandwidth Brain Computer Interface Primary mentor: Ahsan Habib Faculty advisor: Prof. Ahmet Ali Yanik Location: Remote/online Number of interns: 3Project description: Understanding how networks of neurons perform complex computations is one of the greatest scientific, engineering, and medical challenges of the 21st century. This goal remains inaccessible within the realm of electronics and demands fundamentally new techniques with significantly improved technical capabilities. In this research project, the mentor’s research group turns to optics since light offers unprecedented (time/wavelength division) multiplexing and information-carrying capabilities. Achieving electrophysiological recordings through optical means, on the other hand, largely depends on our ability to recruit reliable electro-optic translators converting electrophysiological signals into photons. Even after decades of research, state-of-the-art translators cannot provide the high signal-to-noise ratio requirements because of the low photon counts (e.g., voltage-sensitive dyes) or low electric-field sensitivities (e.g., plasmonic nanoantenna). The mentor’s research group recently invented a novel electro-optic mechanism for the translation of electrophysiological signals into strong optical signals with remarkably high sensitivities and signal-to-noise ratios. This novel approach presents a quantum technological leap for label-free optical imaging of electric-field dynamics with high spatiotemporal resolution and can pave the way to highly efficient brain-machine interfaces. Tasks: The SIP interns will work on the design of an implantable electrical field probe for the detection of neural activity. It will be necessary for the interns carry out the following tasks: (1) learning basic neuroscience; (2) learning the Finite Difference Time Domain (FDTD) method; and (3) developing in vivo probes using the FDTD method. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work URL: https://www.yaniklab.science/, URL: https://advances.sciencemag.org/content/5/10/eaav9786.abstract This research project will allow for remote participation by interns.
|
||||||||||||||||||
| ELE-02 | Title: Protection of Silver-based Astronomical Telescope Mirrors Using a Single Layer of Aluminum Oxide Formed by Various Atomic Layer Deposition – Optical and Structural Assessment Primary mentor: Jacob Sands Faculty advisor: Prof. Nobuhiko Kobayashi Other mentor: Brian Giraldo Location: Remote/online Number of interns: 3Project description: Increasing the durability of silver-based mirrors without compromising the optical performance has been a challenge for years in the application of astronomical telescopes. While several successful implementations of silver-based mirrors exist (e.g., the Gemini telescopes), they often suffer from sacrificing the deep blue and UV portions of the spectrum. A single layer of aluminum oxide (AlOx) formed by atomic layer deposition (ALD) will be studied to assess its potential as a protection layer for the silver-based mirrors. The optical properties and structural integrity of the mirrors prepared under various ALD process conditions will be analyzed in detail. Tasks: The SIP interns will participate in the following activities under the supervision of a graduate student: (1) characterize optical properties and surface morphology of aluminum oxide protection layers using spectroscopic ellipsometry and various microscopes; (2) characterize optical properties and surface morphology of the Ag-based mirrors before and after high-temperature high-humidity endurance test; and (3) simulate spectral reflectivity using the transfer matrix method in conjunction with the effective medium approximation. Required skills for interns prior to acceptance: Some computer programming experience preferred Skills intern will acquire/hone: Computer programming; lab work Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| ELE-03 | Title: Fano-Resonant Biosensing Using Finite-Difference-Time-Domain (FDTD) Primary mentor: Mustafa Mutlu Faculty advisor: Prof. Ahmet Ali Yanik Other mentor: Ahsan Habib Location: Remote/online Number of interns: 2Project description: Nanohole arrays (NHAs) are a class of nanostructured material consisting of nanoscale voids fabricated on the surface of a metallic material (O’Mahony, 2011). Researchers do flow-through experiments to accumulate bioparticles on top of the nanoholes and then measure the characteristic changes. Measuring the change in the light spectrum through nanoholes is a reliable method. These plasmonic nanohole arrays exhibit extraordinary light transmission (EOT) spectra and that spectra enable a few unique ways for biosensing. The SIP interns will be doing some basic simulations about nanohole arrays and their optic/plasmonic characteristics. These simulations will be compared to actual experimental data that has been collected previously. Tasks: The SIP interns will learn about: (1) biosensing technologies; (2) nanohole arrays (NHAs) and their use in biosensing; (3) the FDTD (finite-difference-time-domain) method; and (4) the basics of the LUMERICAL photonics software package. The interns will work with the mentor to simulate the characteristics of NHAs using the LUMERICAL photonics simulation software. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work URL: https://www.yaniklab.science/ This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Environmental Studies[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ENV-01 | Title: Improving Coastal Prairie Restoration for Increased Resilience to Drought Primary mentor: Justin Luong Faculty advisor: Prof. Michael Loik Location: UCSC Main Campus Number of interns: 4Project description: Ecological restoration seeks to alleviate loss of unique ecosystems through native plant reintroductions and invasive species control. However, restoration outcomes can be unpredictable and may become more so with climate change. The mentor’s research group is interested in exploring new methods to improve restoration success in coastal prairies to improve coastal ecosystem resilience to droughts. The group has planted native plant species under rain-out shelters designed to simulate a 1-in-100 year drought. The group is interested in understanding if plant traits and evolutionary relationships are predictive of plant survival and growth. The mentor’s research group is also interested in whether plant traits can explain changes in plant communities. The SIP interns will be working in a lab and will be required to complete basic lab safety training. Work will take place at the UCSC Main Campus and the Coastal Campus. Tasks: The SIP interns will work on analyzing previously collected leaf samples for various leaf functional traits using the free imaging software: ImageJ. Leaf samples were previously collected from numerous plants along the California Coast. Understanding how leaf traits vary along a climatic gradient or within plant families can be important for improving ecological restoration and conservation by informing which species may be best suited for their local environment. The interns will meet regularly with the mentor to learn proper measurement techniques and various lab activities. The SIP interns will read a scientific journal article once every 1 to 2 weeks for group discussion. By week 5, students will begin learning the basics of data analysis to prepare for their final SIP presentation. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work; statistical data analysis; image analysis programming
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Linguistics[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| LIN-01 | Title: Investigating Taste and Perspective in Conversation Primary mentor: John Duff Faculty advisor: Prof. Pranav Anand Location: Remote/online Number of interns: 2 Project description: What do you mean when you say a slice of pizza is “tasty,” a day at the beach was “fun,” or a poem is “beautiful”? And what does it mean when a friend disagrees with you? How do we decide who is right – or can you both be right? Words like “tasty” pose big questions about how humans understand truth and personal experience, questions that are important for researchers who study the structure of meaning in language (semantics). It turns out that with the right type of analysis, we can answer these questions! The goal of this research project will be to carefully examine transcripts and recordings of people having these kinds of arguments, and the ways they are resolved. This kind of detailed investigation will help us learn more about how humans talk about truth and opinions. Tasks: The SIP interns will learn how to use scientific tools to study language. Parts of this will involve reading lots of conversations and writing about them. But just because the mentor’s research group studies words doesn’t mean they don’t use numbers! The interns will also use scientific software to investigate those recordings, and write code to design professional graphs. Throughout the internship, the SIP interns will also get to study language generally. The skills the interns will learn will be useful for anyone interested in linguistics, foreign languages, psychology, or computer science. In order to facilitate remote communication and contributions to the project, the SIP interns must each have daily access to a computer with a webcam, a reliable internet connection, and ideally at least two Gb of free memory. They should have the ability to install new programs on this computer (the mentor will train them in the use of programs like Praat, ELAN, and RStudio), and be comfortable sharing their screen for training purposes. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis URL: https://linguistics.ucsc.edu/about/what-is-linguistics.html Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| LIN-02 | Title: Negative Shifting in Mainland Scandinavian Languages Primary mentor: Myke Brinkerhoff Faculty advisor: Prof. Ivy Sichel Location: Remote/online Number of interns: 2 Project description: In many of the languages spoken around the world, words are only allowed to appear in a specific fixed order. However, languages spoken in mainland Scandinavian are a well-known exception to this constraint on word order, with pronouns being allowed to shift to a position outside of the verb phrase. In addition to pronouns shifting, negative indefinites (e.g., ‘nobody’ or ‘nothing’) are also allowed to shift to positions quite similar to the one that pronouns occupy when shifted. This research project is interested in asking why negative indefinites would behave like pronouns and do they genuinely behave the same as personal pronouns. These questions will be answered by collecting data using computer code specifically written to search through a database of Swedish speeches for instances of these negative indefinites. Tasks: The SIP interns will learn how to apply the scientific method to language. This means that interns will learn how to think critically, how to formulate hypotheses, and how to test those hypotheses about some aspect of language. The interns will learn how to minimize potential confounds during data collection, while also learning how to write computer code to collect that data. If there is enough time, the SIP interns will also learn how to analyze audio recordings using computer software for prosodic evidence of the phenomena under investigation. The interns will also be asked to read and discuss relevant research articles to prepare them to think critically about the data. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; linguistic analysis; data analysisLab work URL: https://linguistics.ucsc.edu/about/what-is-linguistics.html Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Molecular, Cell & Developmental Biology[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MCD-03 | Title: Characterizing the Role of hnRNP-A2/B1 in Immune Regulation Primary mentor: Mays Mohammed Salih Secondary Mentor: Tanya Ivanov Faculty advisor: Prof. Susan Carpenter Location: Remote/online Number of interns: 3Project description: The innate immune response is the first line of defense against pathogens. The proper activation of this response is essential for resolving infections; however, uncontrolled activation could be deleterious and lead to a host of autoimmune diseases. The mentor’s lab is studying how an RNA processing protein, hnRNP-A2/B1, regulates the innate immune response in mice and humans. The mentor’s research entails deleting this protein from macrophages (immune cells) in mice, assessing protein production levels to estimate deleting efficiency, and assessing the change in immune response using different benchtop techniques. The mentor will implement an online teaching protocol where the SIP interns will utilize online/bioinformatics tools to study and characterize the RNA processing protein, hnRNP-A2/B1, and its role in immune regulation. Tasks: The SIP interns will be guided through a literature search using scientific databases to study the known structure and functions of the hnRNP-A2/B1 protein. The interns will be required to independently read and critically analyze scientific papers, participate in weekly discussion and Q&A sessions, formulate hypotheses, and design experiments to answer specific questions. The SIP interns will work in groups on weekly tasks, using databases and bioinformatics tools such as the UCSC genome browser to gather information about the gene of interest to answer specific questions about its structure and function. The interns will look for transcripts, design PCR primers, confirm primer design, analyze PCR results, and draw conclusions about the associated experiments. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work URL: https://mcd.ucsc.edu/faculty/carpenter.html Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| MCD-04 | Title: What do Neurons Say? Decoding the Brain with Statistical and Computational Methods Primary mentor: Yufei Si Faculty advisor: Prof. David Feldheim Location: Remote/online Number of interns: 3Project description: “If the human brain were so simple that we could understand it, we would be so simple that we couldn’t.” Yet, neuroscientists are making significant progress in understanding the brain, and one of the first steps is to decode the neuronal code that our brain uses. We now know that neurons use electric signals as their language to communicate, and these signals can be recorded using in vivo electrophysiology techniques. However, how do we know what these neurons are talking about with their electric signals? The SIP mentor and interns will find out using statistical and computational methods. The interns will gain basic knowledge about the central nervous system, become familiar with basic ideas about physiology techniques, and learn about data analysis and programming. Tasks: The SIP interns will gain a basic understanding of the nervous system, learn about basic ideas of how to study the brain using available techniques, and practice basic computational analysis with existing electrophysiology data. Specifically, the SIP interns will take part in the following: (1) reading primary papers/textbooks from the field and understanding some general concepts of neuroscience; (2) understanding the logic behind the mentor’s project and experiments being performed; (3) learning about basic statistical and computational tools and understanding the analytical methods being used; (4) analyzing existing data as a final practice/project. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis URL: https://feldheimlab.mcdb.ucsc.edu/index.html This research project will allow for remote participation by interns.
|
||||||||||||||||||
| MCD-05 | Title: Meiotic and Mitotic Chromosome Segregation Primary mentor: Anna Russo Faculty advisor: Prof. Needhi Bhalla Location: Remote/online Number of interns: 2Project description: How do cells ensure that they have the correct number of chromosomes after every cell division? Mistakes in cell division during meiosis or mitosis can lead to cells inheriting an incorrect number of chromosomes, which can result in infertility, miscarriages, genetic disorders, and cancer. The mentor’s lab is interested in understanding how chromosome segregation during meiosis and mitosis occurs so that these errors in segregation are prevented. The lab use a combination of genetics, microscopy, and biochemistry to better understand these two processes using the nematode Caenorhanditis elegans (C. elegans) as a model organism. Tasks: The SIP interns will gain a basic understanding of molecular and cellular biology. Potential experiments will include: (1) sing CRISPR/Cas9 gene editing to create florescent proteins or mutations of interest; (2) setting up genetic crosses and using Polymerase Chain reaction (PCR)/gel electrophoresis to genotype worms; and (3) performing either live microscopy to film cells undergoing mitosis or immunofluorescence to visualize meiotic chromosomes. The interns will also learn how to analyze and interpret their data, perform statistical analysis to assess significance, and plan and document experiments. The interns will also be highly encouraged to attend and participate in lab meetings, journal clubs, and learn how to read primary literature from the field. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work; statistical data analysis URL: https://www.bhallalab.com Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| MCD-06 | Title: Microbes, Amyloids, Evolution, and the Origins of Life on Earth Primary mentor: Amanda Carbajal Faculty advisor: Prof. Lynn Rothschild Location: Remote/online Number of interns: 3Project description: The details surrounding the origins of life on earth remain a mystery. We know, thanks to modern technological examination of microbial and geological fossil records, that the environment on earth when life emerged was hostile to life and unlike the earth we live in now. How could life have emerged in these hostile environments? We postulate that amyloids and prionogenic amyloids assisted the Last Universal Common Ancestor LUCA to survive these extreme environments by offering a physical shield-like entity and harboring transmissible phenotypic data. Nucleic acids like DNA and RNA are essential to life but their chemistry is highly sensitive and would have struggled greatly to stay stable and viable in these extreme environments of temperature, acidity, atmosphere components, and UV radiation. Prionogenic amyloids are UV resistant and can be passed among individuals in a species. They are associated with negative effects in mammals and humans via neurodegenerative diseases like Mad Cow Disease but are found in a myriad of other species that are evolutionarily older. Prions themselves are proteins that harbor transmissible information and cause protein folding changes and are not toxic in yeast and other microbes. Additionally, these prion amyloids harbor positive effects that be turned on like molecular switches to assist organism survival when triggered by environmental stress. The mentor’s research group hopes to understand these components in microbes, the oldest living entities on planet earth. Studying them will provide insight into many disciplines, shedding light on evolution, prions, amyloids, their effects on mammals versus microbes, and how they may have assisted LUCA, which gave rise to the three domains of life. Utilizing bioinformatics, the mentor’s group has scanned all annotated genomes to find potential protein candidates across species that could harbor prion amyloids based solely on their genetic code. Tasks: The SIP interns’ primary task will be to develop a helpful in-house database of the microbe species grouped into those that are confirmed, not yet confirmed, and negative for prion amyloids. This database will be used to track genetic drift among specific protein functions across all domains of life (Eukarya, Bacteria, Archaea). The interns’ secondary tasks will include learning what it means to be a scientist from reading peer-reviewed scientific journals, identifying strong and weak studies, and familiarizing themselves with the methods used in the field to achieve the proving of a hypothesis. The SIP interns will learn to network, collaborate, communicate, and see a project through. The interns will learn about a field that is emerging and one that few, if any, other labs are working on. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis; experimental design and protocols URL: https://www.nasa.gov/content/research-overview Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Microbiology & Environmental Toxicology[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MET-01 | Title: Genome Analysis of a Novel Photoarsenotroph, Rhodobacter sp. str. ORIO. Primary mentor: Sanjin Mehic Faculty advisor: Prof. Chad Saltikov Location: Remote/online Number of interns: 3Project description: Arsenic is a naturally occurring poison found in nature. The mentor’s PhD project is focused on studying a process where bacteria use photosynthesis and arsenic to grow, called “photoarsenotrophy”. One day, the mentor’s research group hopes to understand how arsenic is transformed in nature so that they can protect life from arsenic poisoning. This summer, the SIP mentor and interns will perform bioinformatics, which means they will use computer software to perform their analyses. Specifically, the mentor’s research group wants to better understand the genes required for photoarsenotrophy. The SIP interns will ultimately learn how a bacterial genome is sequenced and analyzed. Specifically, the interns will do DNA/protein alignments, create phylogenetic trees, and design genetic engineering experiments. Tasks: The SIP interns tasks will include: (1) bacterial genome assembly/annotation, (2) alignments, (3) phylogenetics, and (4) genetic engineering design. The interns will learn how to search for the bacterial genes of interest, and create a list that can be used as a reference database. The SIP interns will then use the reference database to search large environmental data sets for particular genes of interest. Lastly, the interns will generate a report on the metabolic traits of a bacteria by analyzing its genome and looking for metabolic pathways. Required skills for interns prior to acceptance: Computer programming; biology/DNA knowledge Skills interns will acquire/hone: Computer programming; statistical data analysis This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Ocean Sciences[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| OCS-01 | Title: Relationship of North Pacific Marine Heat-Waves to Climate Extremes in North America Primary mentor: Dr. Aikaterini Giamalaki Faculty advisor: Prof. Claudie Beaulieu Location: Remote/online Number of interns: 2Project description: Climate change has already had noticeable impacts on our environment. Effects that have been previously predicted, such as extreme heat waves and droughts, are now occurring. Understanding extreme temperature events in the ocean as well as on land has been a major scientific concern. Extremely increased land temperatures have been reported in the last decade over North America. At the same time, the most extreme sea surface temperatures have also been documented in the North Pacific and the California Current. For example, 2016 has been the hottest reported year in North America, closely following the 2013–2015 extended marine heat-wave in the Northeast Pacific, named as ‘the Blob’. Nevertheless, little is known about the relationship between those marine and land heat-waves. The mentor’s research group focuses on quantifying these extreme events and further exploring the dynamical relationships between them. The group uses statistical and dynamical techniques applied on observations and modeled output in order to answer questions regarding the time and space that marine and land extreme events occur, and the physical mechanisms that may explain the development of such events. Tasks: The SIP interns will: (1) understand the basics of climate dynamics and the physical relationship between specific oceanic and atmospheric parameters through a literature review of the topic and discussions with the mentors; (2) learn basic programming using Python and/or R; (3) collect and process the publicly available observational datasets and/or model output such as sea surface temperature, land air temperature, sea level pressure, and wind; and (4) apply statistical methods/extremal networks in order to describe possible physical relationships. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Physics[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PHY-02 | Title: Fabrication of Two-Dimensional Electronic Devices Primary mentor: Ryan Tumbleson Faculty advisor: Prof. Jairo Velasco, Jr. Location: Remote/online Number of interns: 2Project description: Researchers are hitting a fundamental limit for how small and powerful electronics can be with our current technology. In this research project, the mentor and SIP interns will create and explore some of the smallest electronic devices in existence and study the exotic behavior of these devices that result from quantum mechanical phenomena. By stacking multiple layers of two-dimensional materials (thickness of one to a few atoms) on top of each other, the group will engineer devices that have novel properties that they can exploit and potentially implement in future nanotechnology. Tasks: The primary objective of this research project is to create and understand the physics behind two-dimensional devices. The mentor will be in the lab fabricating devices while simultaneously live streaming the process and discussing it with the SIP interns. The mentor will provide an in-depth description of the current methods used to cut chips, pre-process them, pick up the two-dimensional materials using scotch tape (yes, just regular scotch tape!), stack them on top of each other, post-process them, and then characterize them. In addition to this, the interns will collaborate on processing the data obtained from characterizing equipment such as an atomic force microscope and a scanning tunneling microscope. These two microscopes provide a way to visually see the surface of a material at the atomic scale. Finally, there will be a Python coding portion of the project where the mentor will cover basic coding methods, fundamental calculations to the research area, and then investigate theoretical properties of the devices being fabricated to better understanding the underlying physics. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work URL: http://jvjlab.sites.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PHY-03 | Title: Dielectric Response in Multiferroics and Novel Dielectrics Primary mentor: Maverick McLanahan Faculty advisor: Prof. Arthur P. Ramirez Location: Remote/online Number of interns: 2Project description: Dielectric materials are electrical insulators that polarize in the presence of an electric field. These materials are essential in energy storage applications and for improving semiconductor devices. This project will investigate the dielectric responses and electrical conduction mechanisms in multiferroics (materials with both electric and magnetic order) and novel dielectrics (e.g., titanates which may exhibit large dielectric constants). Multiferroics may display strong magnetoelectric coupling such that applied magnetic fields could be used to alter their dielectric properties, and materials with large dielectric constants will increase energy storage capabilities. Finding materials that possess either of these properties may ultimately result in potential candidates for future device applications. Tasks: This research project will consist of lab-work, software-hardware integration, and experimental data analysis. SIP interns will learn how to prepare crystal samples for dielectric measurements in cryostats – i.e., crystal orientation, cutting/polishing, and metal deposition. Measurements will be performed as a function of AC voltage source frequency and applied magnetic field, from room to liquid helium temperatures (300 K to 4 K). The interns will integrate data collecting software with cryostat hardware to run experimental trials. The experimental data will then be modeled to dielectric relaxation models to characterize the samples. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis URL: https://aprlab.sites.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PHY-04 | Title: Synthesis and Characterization of a New Two-Dimensional Material Heterostructure/Composite via Chemical Vapor Deposition Method Primary mentor: Ashlyn Molyneaux Faculty advisor: Prof. Aiming Yan Location: Remote/online Number of interns: 3Project description: Two-dimensional materials like graphene, boron nitride, and transition metal dichalcogenides (TMDs) have been of growing interest recently due to their novel chemical and physical properties. The materials are classified as 2D because they have a thickness of only one or a few atoms. There are many potential and promising applications of these materials in next generation flexible electronics. In order for these applications to be feasible, controllable and scalable syntheses of these materials are necessary. Atomically thin molybdenum disulfide (MoS2) is the TMD of interest for this research project. Under close mentoring and supervision, the SIP interns will learn the chemical vapor deposit growth method for controllable synthesis of this material and together the mentor and interns will work to further develop this method. The interns will then learn to use techniques such as optical microscopy, atomic force microscopy, and Raman spectroscopy to further understand and characterize this material. Tasks: First, the SIP interns will learn the growth method. Then, the interns will learn characterization techniques like optical microscopy, atomic force microscopy, and Raman spectroscopy. From weeks 4-7, the interns will use the CVD growth method to grow MoS2 and tweak growth parameters to get the best yield of the material. Each intern will learn each task well enough to perform it independently. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work URL: https://sites.google.com/a/ucsc.edu/2300-delaware/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PHY-05 | Title: Terrestrial High-Energy Observations of Radiation (THOR) Deployment Site Research Primary mentor: Jeffrey Chaffin Faculty advisor: Prof. David Smith Location: Remote/online Number of interns: 3Project description: In 1994, a NASA spacecraft, the Compton Gamma-Ray Observatory, observed several very bright and very fast bursts of gamma radiation originating in Earth’s atmosphere. It has been found that these intense bursts of radiation are associated with lightning strikes and that the large electric fields generated in thunderclouds and at the tips of lightning leaders can act like natural particle accelerators several kilometers in length. These electric fields are capable of accelerating the free electrons in our atmosphere to relativistic speeds, and the subsequent collisions of these highly energetic particles with atmospheric nuclei results in the emission of gamma radiation. While this radiation takes several forms, the most dramatic and important are terrestrial gamma-ray flashes (TGFs). TGFs are bursts of gamma radiation (and byproducts such as neutrons and positrons) associated with a small percentage of lightning flashes and lasting less than a millisecond. During that brief time, TGFs are about as luminous in gamma-rays as the entirety of Earth’s atmosphere (which glows in gamma radiation from interactions of cosmic rays in air). This is incredibly bright and occurs just a few kilometers above us! In the part of a thundercloud where TGFs are generated, they might produce a radiation dose of up to 1 sievert, sufficient to produce immediate radiation sickness and a high risk of later cancers in humans. The mentor’s research group specializes in ground and in-situ (balloon and airplane) observations of TGF events, and they are currently in the process of designing a suite of new ground based detectors, the Terrestrial High-Energy Observations of Radiation (THOR) instruments, to improve their observations of TGF events in low altitude storm systems. A critical part of any field work is determining the optimum location to place each instrument. One needs to consider, tropopause height as it relates to storm altitudes, lightning frequency, TGF frequency based off satellite data, and current research into lightning processes and power per flash studies (Superbolts), as well as the possibility of tower locations (i.e., lightning rods), other infrastructure, and ease of access. This research incorporates particle physics, lightning physics, and general atmospheric science with an emphasis on instrumentation and field deployments. Tasks: The SIP interns will work remotely and be given the job (under the mentor’s supervision) of researching optimal field deployment locations for the new THOR instruments. This will be accomplished by a combination of data analysis and programming to create world maps that correlate weather system altitude patterns, lightning frequency, and TGF frequency from satellite data and current research on “superbolts” by Holzworth (2019) of the World Wide Lightning Location Network. Additionally, the SIP interns will need to engage in high level internet research to determine country by country information on communication tower distributions, infrastructure, and possible organizational contacts. On a daily basis, the SIP interns can expect to do the following: (1) work in a Python coding environment to parse large data sets and create global heat maps; (2) engage in research and information gathering via the internet; (3) document and summarize all information gathered to present to research group members on a weekly basis; (4) investigate “superbolt” data from Holzworth (2019) in the framework of possible field sites; (5) maintain a detailed laboratory notebook; and (6) participate in research group meetings. Required skills for interns prior to acceptance: Computer programming (some knowledge of a coding language, preferably Python) Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_title size=”3″]Psychology[/fusion_title][fusion_text]
| Code | Research Project Descriptions | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| PSY-01 | Title: World of Robots: Child-Robot Interactions Primary mentor: Elizabeth Goldman Faculty advisor: Prof. Su-hua Wang Other mentor: Sam Basch Location: Remote/online Number of interns: 3 Project description: Robots are becoming a major part of our society. This research project aims to investigate how young children interact with robots. This is an important topic because many robots are being designed and marketed for children. However, we do not understand how these robots impact children and their development. In this research project, children will watch a robot perform different behaviors, and the SIP interns will then observe the children’s reactions and take detailed notes. After the robot exhibits these different behaviors, children will watch the robot attempt to complete a task and will then be given the opportunity to help the robot finish the task. This research project has already been designed. This summer, the mentor’s research team will work together to collect as much data as possible. The SIP interns and the mentor’s research group will then work together to code and analyze the data they have collected. This research project could impact how robot designers create and build robots for young children. Tasks: This research project is for SIP interns who are interested in learning about robots and who would like to work with children and families. No previous experience working with children is needed, as the interns will be taught how to work with children. The SIP interns will also learn valuable skills such as naturalistic observation, taking detailed notes, eye tracking (tracking the eye movements of young children), and data analysis. The interns will help set up the study, run the study, enter data, and analyze the data. In terms of data analysis, this research project will involve coding child behaviors and reactions. It will also involve coding those behaviors that the SIP mentor and interns have observed. The interns will be trained in coding and observation of videos, survey data, and interviews. The interns will see the research process from start to finish and will gain valuable experience of (remotely) working in a psychology research lab. SIP interns will also learn about designing a research proposal, formulating a research question, and conducting a literature review on a topic of their interest. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Remote lab work; statistical data analysis URL: /https://elizabethgoldman.weebly.com This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-02 | Title: Reciprocity in Conversation Primary mentor: Andrew Guydish Faculty advisor: Prof. Jean E. Fox Tree Location: Remote/online Number of interns: 3Project description: Do people work together to create reciprocal balances across conversations? The SIP mentor is interested in conversational dynamics and how people carry and maintain conversations. In particular, the mentor is interested in conversational balance between participants throughout the course of the conversation, and how these balances influence how individuals communicate with one another. Tasks: The SIP interns will work on numerous aspects of development regarding psychological experiments. The interns will work with the mentor in the development of experiments examining areas of interest pertaining to cognitive psychology (e.g., discussing experimental design, conducting literature reviews on related concepts), work with real data (e.g., transcribing videos, examining transcripts), as well as running participants in psychological experiments under supervision. Through this process, the SIP interns will gain experience in the following: writing APA style annotated bibliographies; processes associated with experimental development; running human participants; analyzing real data in IBM’s SPSS; and development and use of Python algorithms for data parsing and analysis. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis URL: https://guydish.sites.ucsc.edu, https://foxtree.sites.ucsc.edu This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-03 (a,b) | Title: Understanding Misophonia: What is It and How Do the Senses Interact? Primary mentors: (a) Allison Allen (b) Chris Kay Faculty advisor: Prof. Nicolas Davidenko Location: Remote/online Number of interns: 4Project description: Do you or does anyone you know experience sensitivity to particular sounds, such as chewing or sniffling? Some people who experience a condition called misophonia report sensitivity to certain sounds that may not bother others, such as a person chewing, sniffling, or tapping. Hearing such sounds can cause the person to experience averse physical and emotional reactions that can interfere with everyday life. Despite the impact that misophonia can have on people’s lives, little work has been done to characterize and treat the condition. The mentors’ research will focus on characterizing misophonia and exploring how information from other senses (e.g., vision) can influence the misophonic experiences. As described below, there will be two sub projects, (a) and (b), within the same larger research project. Tasks: The SIP interns will have the opportunity to learn about misophonia and related perceptual processes, including vision and audition, and how processes can interact. This will be done by reading scientific articles each week and discussing them with the mentors. They will also: (a) gain experience collecting data in an online experiment and will learn how to program and analyze qualitative data using MATLAB; and (b) prepare audiovisual stimuli and use it to run a quantitative experiment. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis URL: https://davidenko.sites.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-05 | Title: Exploring Everyday Helping Primary mentor: Margie Martinez Faculty advisor: Prof. Audun Dahl Other mentor: Charles Baxley Location: Remote/online Number of interns: 2Project description: How do we come to help others? The mentor’s research group examines moral reasoning in relation to one’s actions in everyday contexts. The group is particularly interested in how parent-child interactions influence the development of helping behavior and how this may vary across different cultural backgrounds. This research project will examine how the daily routines of families impact judgments, reasoning, and decisions about helping behaviors. By examining the everyday experiences with helping, the interns and mentor can gain a better understanding of how children and adults come to the moral decision of who and when to help. Tasks: The SIP interns will be involved in most or all aspects of this research project. The interns may help design research studies, collect data (for instance, through interviews), analyze video recordings or interview transcripts, and/or discuss research articles. The interns may work with data from past or current projects exploring how children and young adults think about helping. The research group will discuss literature relevant to the project and moral development. This research project will provide an opportunity for interns to learn about and contribute to all stages of psychological research. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work; statistical data analysis; field work URL: https://esil.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-06 | Title: Children’s Learning Through Collaboration Primary mentor: Samantha Basch Faculty advisor: Prof. Su-hua Wang Other mentor: Elizabeth Goldman Location: Remote/online Number of interns: 2Project description: The mentor’s research focuses on how toddlers and preschoolers learn through collaboration. This summer, the mentor’s research team will study parent-child collaboration during play. The team will study both natural play and structured play, with a special focus on parental question-asking. The hope is the results will shed light on how culture and context shape parent-child collaboration and learning. Tasks: The SIP interns will get experience with the full range of activities that occur in a developmental psychology lab, including scheduling, explaining informed consent, and running experiments. The interns will also learn how to collect and analyze observational data. These are important skills for any psychologist. Finally, the interns will have the chance to work with other members of the Infant and Child Development Lab on ongoing projects. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Statistical data analysis; field work URL: https://suhua.sites.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-07 | Title: Exploring How Moral Reasoning Develops Over the Lifespan Primary mentor: Charles Baxley Faculty advisor: Prof. Audun Dahl Other mentor: Margie Martinez Location: Remote/online Number of interns: 3Project description: Children, adolescents, and adults reason and make judgments about what is right and wrong. The mentor’s laboratory investigates how individuals at different ages reason and judge about moral issues, and how their judgments relate to their actions. The mentor’s research group studies how children and adults behave in different situations and interview them about their thoughts and feelings. For instance, why do young children think it is good to help others and bad to harm others? Why do students sometimes decide to cheat in school, even though they think it is generally wrong to do so? The overall goal of the mentor’s research is to understand how people make judgments and decisions surrounding right and wrong, and how one can help people make better decisions. Tasks: The SIP interns may help develop a new research project, as well as work on existing research projects. As part of this process, the interns will learn to develop theory by diving into the moral development literature and may also help develop interview protocol and materials. To gain experience with data analysis, the SIP interns will work with data from past projects that have explored topics such as academic misconduct. There will be weekly team meetings where the research group will discuss past literature related to the project and overarching theory. This research project provides an excellent opportunity for the SIP interns to learn about all stages of psychological research, from discussing scientific articles to reporting results. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Statistical data analysis URL: https://esil.ucsc.edu/ This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-08 | Title: Human and Artificial Agent Communication Primary mentor: Elise Duffau Faculty advisor: Prof. Jean E. Fox Tree Location: Remote/online Number of interns: 2Project description: As technology advances, artificial agents, such as Alexa and Siri, are becoming more and more integrated into our lives. The mentor is interested in expanding on how we communicate with artificial agents. More specifically, the mentor is interested in understanding the different ways in which we communicate with artificial agents, and how we can manipulate artificial agents’ communication styles to adapt to more casual interactions. Tasks: The SIP interns will gain experience in the various aspects of psychological experiments. The interns will work with the mentor in learning how to conduct research in cognitive psychology related to the area of interest. This will include engaging in experimental design, conducting literature reviews, working with data, and running participants in a psychological study using online methods with supervision. The SIP interns will gain experience in writing APA style annotated bibliographies, how to design an experiment, running online surveys, and analyzing data in SPSS, R, and Python. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; lab work; statistical data analysis Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-09 | Title: Gender, Orientation, and Identity in Online Roommates Ads Primary mentor: Daniel Copulsky Faculty advisor: Prof. Phillip Hammack Location: Remote/online Number of interns: 3Project description: Many college students and working adults find roommates online, with ads posted to sites like Craigslist, Facebook, and Reddit. Along with details about pricing and amenities, many ads mention personal info and values. Posters often hope to match with roommates based on identities like gender, sexual orientation, political affiliation, or dietary restrictions. This research will look at how individuals describe both their own identities and their preferences for potential roommate identities. Tasks: The SIP interns will: (1) read and discuss scholarly articles related to identity, gender and sexuality, bias and discrimination, and housing selection; (2) gather data from roommate ads posted to sites like Craigslist, Facebook, and Reddit; (3) read roommate ads, code identity references, and look for emerging themes; (4) analyze these codes to look for trends, including regional differences in ads; and (5) collaborate on ideas for a possible future experimental study looking at how individuals respond to identity preferences stated in housing ads. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Statistical data analysis; qualitative data analysis URL: https://psychology.ucsc.edu/about/people/grad-directory.php?uid=dcopulsk This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-10 | Title: Exploring the Boundaries of Human Memory Primary mentor: Mercedes Oliva Faculty advisor: Prof. Benjamin Storm Location: Remote/online Number of interns: 2Project description: Memory serves a purpose in most aspects of our lives. That is the approach that the mentor’s research group takes, allowing a broad range of research questions. Specifically this summer, however, the SIP mentor and interns will be working on (at least) three projects, two of which consider the boundaries of retrieval-induced forgetting and retrieval-induced facilitation (specifically, feedback and expertise), and the third considers the various ways in which memory processes may function differently in ADHD populations. Depending on whether it will be possible to work with participants in-person, the mentor and interns may also return to a research project the considers the relationship between creativity, task switching ability, and memory. Tasks: The SIP interns will develop their critical reading skills, something that will serve them well in future academic endeavors. The interns will learn about all stages of a research project, from design and construction of study materials, to data collection, to data entry and management and basic statistical analyses. Depending on whether it is possible to run participants in-person, the SIP interns may have the opportunity to be introduced to various neuropsychological assessments with hands-on data collection. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Statistical data analysis; study design URL: https://people.ucsc.edu/~bcstorm/research.html Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-11 | Title: Texting, Video Chat, and Emotions Primary mentor: Vanessa Oviedo Faculty advisor: Prof. Jean E. Fox Tree Location: Remote/online Number of interns: 2Project description: The mentor’s research interests lie in the domain of technology assisted communication. Specifically, the mentor is interested in the way that people communicate and emotionally connect over different communication mediums, such as face to face, video chat, and texting. The current research project is examining differences in emotional communication when people interact via video chat versus text-based conversations. Tasks: The SIP interns will work with the mentor in the completion of experiments by reviewing experimental design, conducting APA style literature reviews, and completing APA style annotated bibliographies. The interns will also work with real data in which they will transcribe audio files, examine transcripts, enter and clean quantitative data using SPSS, and code qualitative audio files. In working with the mentor, the SIP interns will learn skills such as designing a research study, completing a literature review, creating research questions and developing hypotheses, entering quantitative and qualitative data, and analyzing the final data set. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work; statistical data analysis Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-12 | Title: Communication in Varying Mediums Primary mentor: Ryan Pili Faculty advisor: Prof. Alan Kawamoto Location: Remote/online Number of interns: 3Project description: Recent advances in technology have provided new ways to communicate with others. Mediums such as video-chatting, instant-messaging, and voice-messaging each provide their own constraints on peoples’ conversations. How could these constraints influence how people communicate? This research project is a psycholinguistics study investigating how people might adapt their conversations to a given medium. The mentor’s goal for this project is to find possible sources of face-to-face and computer-mediated communication, to analyze differences in how people communicate. This research project is ideal for SIP interns who are interested in cognitive science, linguistics, computer-mediated communication, human-computer interaction, and video-games. Tasks: The SIP interns will learn to read research articles under the mentor’s guidance to understand the background of the project. With this context, the interns will code video and speech data of conversations for analysis. The SIP interns may also edit video-data, carry out preliminary data analysis, do online recruiting and scheduling of human participants, and administer computer experiments under the mentor’s supervision. The interns will gain hands-on experience with data visualization (MATLAB), video editing (Adobe Premiere), phonetics software (PRAAT), and face-recognition software. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Computer programming; statistical data analysis This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-13 | Title: Understanding Spontaneous Communication Primary mentor: Allison Nguyen Faculty advisor: Prof. Jean E. Fox Tree Location: Remote/online Number of interns: 3Project description: Why do we use the words that we use, and do we signal specific things with our choices? It is possible that specific discourse markers are used in specific contexts. The mentor is interested in how and why information and stories spread through populations. The mentor is also interested in other aspects of spontaneous communication and how people talk to one another. Tasks: The SIP interns will code data, run statistical analysis on data collected, and transcribe videos. They will also be asked to read and discuss current literature in the area of cognitive psychology, especially in the area of communication and the spread of information. The SIP interns will be asked to write up brief reports and will be given training in APA-style writing. The interns will have the chance to learn about running psychology experiments using Google Forms and LimeSurvey and will get experience working with Excel and possibly Python. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Transcriptions; data coding; computer programming (depending on interest) URL: http://www.allisongnguyen.wordpress.com This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-14 | Title: Service-Learning Classes and College Student Outcomes Primary mentor: Miguel Lopezzi Faculty advisor: Prof. Regina Langout Location: Remote/online Number of interns: 3Project description: Service-learning classes are important because they help students learn while they are also engaged in the community and giving back. But, not all service-learning courses are the same. Yet, they are often treated the same in the research literature. In this research project, the SIP mentor and interns will work together to figure out differences across several service-learning courses to see if these differences help them to understand college student outcomes better. For example, are certain kinds of classes related to certain kinds of outcomes (academic vs. civic engagement[/fusion_text][/fusion_builder_column][fusion_builder_column type=”1_1″ type=”1_1″ background_position=”left top” background_color=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding_top=”” padding_right=”” padding_bottom=”” padding_left=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none” align_self=”flex-start” first=”true” last=”true” hover_type=”none” link=”” border_position=”all”][fusion_text][e.g., volunteering in organizations])? Tasks: The SIP interns will listen to and transcribe (write down or type out), word for word, interviews between the graduate student researcher and professors who teach service-learning classes. The interns will also check the transcriptions for accuracy, and help to categorize the interviews to determine the quality and nature of the service-learning classes. The SIP interns will learn a lot about interviews, how to work with word data, and different models for service-learning classes. The interns will get to help make important decisions about categorization of the classes. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work URL: http://lopezzi.sites.ucsc.edu This research project will allow for remote participation by interns.
|
||||||||||||||||||
| PSY-15 | Title: Synthetic Monologues and Dialogues Primary mentor: Yasmin Chowdhury Faculty advisor: Prof. Jean E. Fox Tree Location: Remote/online Number of interns: 2Project description: We communicate with synthetic (computerized) voices through various types of technology (e.g., Siri/Alexa) in our daily lives. Due to the increasing nature of this interaction, we want to research the persuasive implications behind these types of voices. In this project, the mentor and SIP interns will experimentally test how different synthetic voices, communicated through monologues and dialogues, influence persuasion and perceived power on various topics. Tasks: The SIP interns will read research papers, complete literature reviews, code data, run experimental participants (with supervision), and transcribe interactions. The interns will have bi-weekly meetings with research teams where they will discuss ongoing and upcoming work. Required skills for interns prior to acceptance: None Skills interns will acquire/hone: Lab work Special age requirement: Interns must be 16 years old by June 22, 2020. This research project will allow for remote participation by interns.
|
[/fusion_text][fusion_separator top=”50″ /][/fusion_builder_column][/fusion_builder_row][/fusion_builder_container]