Katelyn Gao is a Research Scientist in the Intelligent Systems Lab at Intel, working on machine learning. Katelyn received her PhD in Statistics from Stanford University and was funded by a NSF Graduate Research Fellowship. Her research interests primarily lie in understanding and developing algorithms for generalization and robustness, in particular for reinforcement learning. Her work has appeared in venues such as NeurIPS, Statistica Sinica, and the Electronic Journal of Statistics.
Research areas
Algorithms
Artificial Intelligence (AI)
Data Analytics & Modeling
Machine Learning
Reinforcement Learning (RL)