Audrey Huang
Kempner Institute Research Fellow
About
Audrey Huang’s PhD research in Computer Science was advised by Nan Jiang at the University of Illinois Urbana-Champaign. Previously, she received an MS in Machine Learning at Carnegie Mellon University, where she worked on risk-sensitive RL and robotics, and a BS in Computer Science from Caltech, where she worked on protein engineering.
Research Focus
Audrey’s research focuses on developing the scientific and mathematical foundations of interactive decision making in modern-day settings, such as post-training in language models. Looking forward, she is especially interested in investigating the role of reinforcement learning in contemporary LLM training pipelines, as well as in understanding the optimization dynamics of reinforcement learning.