Student-led Projects (click project name for more detail):

**p-rotein: Identifying Intrinsically Disordered Proteins from Primary Sequences (Lead: Michelle Garcia PO ‘22)**

• Identifying protein disordered regions that compose about 50% of the entire human proteome
• Relevant to understanding the underpinnings of protein structure prediction
• Great for folks interested in applying computation to the natural sciences

**p-gaming: Competitive Video Game Outcome Prediction (Lead: Austin Zang PO ‘24)**

• Build a predictive model capable of correctly estimating the win or loss outcome of a competitive video game given in-progress factors
• Learn and apply supervised classification ML (Logit regression, Decision trees, SVM, etc.)
• Extract data using REST API calls and build a csv database
• Explore model selection and model tuning in scikit-learn
• Use machine learning with a fun and approachable video game dataset
• Come work on a supportive and creative team!

**p-resume: Leveling the Employment Playing Field (Lead: Kevin Ayala PO ‘22)**

• Implement and apply updates to web scraper
• Apply Named Entity Recognition model to scraped job listings
• Publish working app using Flask and Docker
• Perfect for anyone wanting full stack experience

**p-generative: Exploring Generative Models of Cognition as Generative Art (Lead: Jacob Zimmerman PO ‘23)**

• Generative models try to infer the algorithm that has produced given data. They can be applied to various problem domains, but they are especially insightful in modeling cognitive processes—the algorithms in our minds.
• Generative art is an art practice in which human artists collaborate with algorithms (often handmade) to produce pieces, typically visual.