
Welcome to CSta
We combine Computer Science, Statistics, AI, Data Science, and Cybersecurity to enhance multidisciplinary learning and research for undergrads and grads. Cross campus and industry collaborations involve faculty, students, scientists, artists, health care researchers, historians, and engineers.
Undergraduate & Graduate Courses
See our courses in Computer Science, Statistics, Data Science, and Cybersecurity ranging from computing foundations to theory and statistics to systems and artificial intelligence.
coursesAnnouncements
[Talk] Harini Suresh: From universal models to local agency: opportunities for more community-controlled AI (1/20/2026) - When: Friday, January 30, 3:00 PM Where: Tyler 055 Abstract As AI systems are increasingly introduced into our everyday lives and high-stakes domains, it’s critical that decisions around their use, design, and governance center the specific contexts and communities they affect. My research explores participatory approaches that support community control, domain specificity, and local agency […]
[Talk] Krishna Venkatasubramanian: Designing for accessibility for adults with intellectual and developmental disabilities around traumatic contexts (12/1/2025) - When: Friday, December 5, 3:00 PM Where: Tyler 055 Abstract There are over 7 million people with intellectual and developmental disabilities (I/DD) in the US. I/DD (e.g., Down syndrome, Williams syndrome, Autism, Smith-Magenis syndrome, etc.) are a set of disabilities that negatively affect the trajectory of an individual’s intellectual, emotional, and/or physical development. The abuse […]
[Talk] Elizabeth Bersson: Feature aware covariance estimation, with application to mixtures of chemical exposures (11/5/2025) - When: Friday, November 14, 3:00 PM Where: Tyler 055 Abstract The motivation of this research is to improve inferences on the covariation in environmental exposures, motivated by data from a study of Toddlers Exposure to SVOCs in Indoor Environments (TESIE). The challenge is that the sample size is limited, so empirical covariance provides a poor […]




