Surbhi Goel

Surbhi Goel is the Magerman Term Assistant Professor of Computer and Information Science at University of Pennsylvania. Prior to this, she was a postdoc researcher at Microsoft Research NYC, and received her Ph.D. in Computer Science from the University of Texas at Austin where her thesis received the Bert Kay Dissertation award. Her research interests lie at the intersection of theoretical computer science and machine learning, with a focus on developing theoretical foundations for safe, reliable, and trustworthy AI. Her group’s research is generously supported by grants from NSF, OpenAI, Microsoft, and UK’s AI Security Institute. Among her honors are a JP Morgan AI Fellowship, a Simons‐Berkeley Research Fellowship, and Rising Star awards in ML and EECS. She is also the co-founder of Learning Theory Alliance (LeT‐All), a community building and mentorship initiative and recently organized the Special Year on Transformers and LLMs at Simons Institute.

AI2050 Project

AI designed to converse and collaborate with people promises immense societal benefits, from medicine to education. Yet, the black-box nature of these systems leads to unpredictable and often harmful errors, undermining the trust essential for their widespread and safe adoption. Goel’s project addresses this trust deficit by using theoretically grounded approaches to understand why these systems fail during conversations, find ways to predict these failures, and empower the system to use these signs to verifiably avoid risky decisions. The goal is to build a future where AI is safe by design.