Want to gain hands-on experience with data science? Ready to apply the skills you’ve learned in the classroom to real world projects? Curious about research opportunities offered by the DSI, and want to prepare for upcoming semesters?
The deadline to apply round 1 for projects will be this Sunday, December 11th at 11:59p. Apply using the Research Interest Form, https://bit.ly/dsi-project-interest. If you’d like to learn more about the projects, see our recorded information session. We’ll be notifying students on Tuesday, December 13 on acceptances.
Project participants work with the DSI’s professional staff of data scientists and project PIs/stakeholders, applying data science skills developed in the classroom, building experience with organizing and executing data science projects, and augmenting their data science skills in a team-based setting.
What are the projects?
Learning New Languages: East Asian Studies
Ever tried to learn a new language and found yourself studying vocabulary that wasn’t helpful for you? In this project, you’ll use NLP, web scraping, and deep learning transformers to build better vocabularies for new language acquisition in Hindi. Lead: Umang Chaudhry
Required: Python (preferred: CS 2204 or above), Transformers/deep learning, Huggingface Datasets or related, Familiarity with Hindi or other uncommon languages
Women’s Basketball
In this project, you’ll continue building a dashboard to help coaches and trainers better tune their training strategies for peak athletic performance of athletes. Lead: Umang Chaudhry
Required: R, Python; R Shiny; API integration, familiarity with Python requests package, json;
Preferred: Familiarity with anomaly detection
Narrative Arc
Have an interest in mathematics, programming, and studying the trajectories and evolution of stories? In this project, you’ll contribute to discovery of new deep learning methods for mapping the behavior of stories. Lead: Jesse Spencer-Smith
Required: Python (CS 2204 or above), transformers, Huggingface datasets, APIs
Transformers for Legal Documents
Have an interest in the law and developing deep learning models and strategies to meet common tasks? In this project, you’ll train a deep learning model for a number of law-related tasks. Lead: Charreau Bell
Required: Python (CS 2204 and above); transformers; strong ability to read, interpret, and use APIs
Preferred: Huggingface datasets
Ancient Mortars
In this project, you’ll use deep learning and transformers to create a model to identify particles composing ancient structures. Lead: Abbie Petulante and Charreau Bell
Required: Python (CS 1100 and above), transformers
Preferred: Python (CS 2204 and above)
Understanding Musicians in Nashville
In this collaboration with the Arts and Business Council in Nashville, you’ll build a dashboard to clearly convey survey results from musicians with their own businesses in Nashville. Lead: Charreau Bell and Jesse Spencer-Smith
Required: R (DS 3100 and above or >1 classes that used R), Shiny or experience with Reactive user interfaces, skill in data visualizations
Preferred: DS 1000 or above; CSET, PSCI, or other courses in visualization; user interface/user experience development
Deep learning with EEG Data (Exploratory)
On this project, we’ll prepare EEG data for modeling with deep learning transformers to better understand responses from a human subjects trial. Lead: Charreau Bell
Required: Python (DS 1100 and above); strong ability to read, interpret, and use APIs
Highly preferred: Python (CS 2204 and above), deep learning transformers, Huggingface datasets, experience with EEG or other signal data (e.g., EE, BME majors)
Deep learning with Laser Interferometer Gravitational-Wave Observatory (LIGO) Data (Exploratory)
On this project, we’ll prepare LIGO data for modeling with deep learning transformers to understand gravitational waves. Lead: Jesse Spencer-Smith
Required: Python (DS 1100 and above); strong ability to read, interpret, and use APIs
Highly preferred: Python (CS 2204 and above), deep learning transformers, physics and astronomy majors, Huggingface datasets, experience with LIGO or other signal data (e.g., PHYS, EE, BME majors)
Deep learning with fMRI Data (Exploratory)
On this project, we’ll prepare fMRI data for modeling with deep learning transformers to better process fMRI data
Required: Python (DS 1100 and above); strong ability to read, interpret, and use APIs. Lead: Charreau Bell
Highly preferred: Python (CS 2204 and above), deep learning transformers, Huggingface datasets, experience with fMRI or other signal data (e.g., EE, BME majors)
What is the time commitment and expectations for participants?
The DSI provides experiential learning opportunities aligned with standard industry practice and adopts an Agile methodology for running projects. This means that you’ll be in about 3 meetings per week, one meeting will be up to 1.5 hours, and the other two are usually 30 minutes to an hour. Outside of these meetings, you’ll be expected to complete (or make meaningful progress) on the tasks you’re assigned during that week using best practices. We want you to have the best learning experience and also meet the project objectives, so we do expect our participants to attend all project meetings; however, we do also understand the occasional absence due to interviews, illness, etc.
Can I get course credit for working on projects?
Depending on the breadth of the project, for some projects you may be able to receive credit through DS 3850 for undergraduates with requirements outlined here. Depending on the number of hours of research credit, you may be expected to take on a larger breadth of responsibilities and requirements. Students may also use this towards Immersion with the DSI, given the requirements described here for the Data Science Trainee Program, again with an augmented set of responsibilities and contribution requirements.
