Speakers & Panelists

Sida Wang
Sida Wang
FAIR
Sida I. Wang is a research scientist at Facebook AI Research (FAIR). Sida researches unsupervised translation, including recent work with reasoning about programming languages.

Shan Lu
Shan Lu
MSR/UChicago
Shan Lu is a professor at the University of Chicago. Her research focuses on software reliability and efficiency, particularly detecting, diagnosing, and fixing functional and performance bugs in large software systems.

Kevin Ellis
Kevin Ellis
Cornell
Kevin Ellis is an assistant professor at Cornell University. He researches the intersection of machine learning, program synthesis, and cognitive science.

Emily First is a postdoctoral researcher at UC San Diego working with Sorin Lerner. She previously completed her PhD at UMass Amherst under Yuriy Brun. Her research is at the intersection of software engineering, programming languages, and machine learning. She focuses on creating tools to automatically generate proofs of software correctness.

Nikitha Rao is a PhD student at Carnegie Mellon University, advised by Vincent Hellendoorn and Claire Le Goues. She researches the use of large language models in code generation and reasoning.

Charlie Snell
Charlie Snell
Berkeley
Charlie Snell is a Ph.D. student at UC Berkeley, advised by Dan Klein and Sergey Levine, whose research focuses on natural language processing, deep reinforcement learning, and the intersection of these fields.

Koushik Sen
Koushik Sen
Berkeley
Koushik Sen is a professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His research interest lies in Software Engineering, Programming Languages, and Formal methods. He is interested in developing software tools and methodologies that improve programmer productivity and software quality.

Xin Zhang
Xin Zhang
PKU
Xin Zhang is an assistant professor at Peking University whose research focuses on program analysis and its intersection with machine learning and artificial intelligence, aiming to enhance the interpretability, fairness, and robustness of software systems.