Bridging Programming Languages, Formal Methods, and Natural Language Processing

Jocelyn Qiaochu Chen is an Assistant Professor in the Department of Computing Science at the University of Alberta and a CIFAR AI Chair affiliated with Amii. Her research lies at the intersection of programming languages, formal methods, and natural language processing, with a primary focus on neurosymbolic approaches for building reliable AI-assisted software systems. She develops methods that combine the flexibility of large language models with the rigor of symbolic reasoning, solvers, and formal verification tools.

Her research explores LLM agents for code, proof, and data tasks, domain-specific languages, and program synthesis, aiming to make AI systems more trustworthy, interpretable, and inspectable. Jocelyn received her PhD in Computer Science from the University of Texas at Austin, where she focused on program synthesis and neurosymbolic systems for end-user programming tasks. Her work is regularly published in top-tier programming languages, NLP, and AI venues, where she also serves as a reviewer. Through her research, she aims to develop AI systems that can synthesize and reason about programs in settings where correctness and human supervision are critical.