Technical AI research and applied machine learning initiatives.
Lead: Obed Pasha
Automatically flagging corrupt or mis-entered data across databases. Extension of last year’s work.
Lead: Dr. Bazzano
Aggregating N-of-1 experimental designs using machine learning and deep learning to model individualized treatment effects.
Lead: Dr. Bazzano
Building an AI agent translating a scoping review of AI in public health into an interactive, accessible system.
Lead: Dr. Bazzano
Designing a privacy-conscious AI prototype supporting women balancing work, caregiving, and health.
Lead: Dr. Bazzano
Developing a multimodal misinformation detection system focused on maternal and child health.
Lead: Dr. Sylvia
Coming soon
Lead: Dr. Sylvia
Coming soon
Lead: Dr. Templin
Build and evaluate models that learn user preferences from feedback (ratings, clicks, comparisons) to optimize rankings and recommendations. Work includes data cleaning, training preference/ranking models, metric-driven evaluation, and an end-of-semester demo/report.
Lead: Dr. Sola
Using NLP to classify how social scientists operationalize neoliberalism across published research.
Lead: Arsh Noman
Using evolutionary algorithms and reinforcement learning to discover QEC codes and reimplement research-grade systems.
Lead: Sam Bisaria
AI-powered course recommendations, autonomous registration tools, and UI improvements integrating ConnectCarolina data.
Lead: Rohan Phadke
Using video understanding models to caption and analyze sports videos. The end goal is to produce a full-stack application that can provide feedback on an athlete’s form as a virtual coach.
AI@UNC