Bingbin Liu
Research Fellow
She/Her
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About
Bingbin Liu is a research fellow at the Kempner Institute. Before joining Kempner, Bingbin was a research fellow at the Simons Institute, and earned her Ph.D. in Machine Learning from Carnegie Mellon University under the supervision of Andrej Risteski and Pradeep Ravikumar. She also spent time studying in Palo Alto and Hong Kong, and grew up in a beautiful ancient city in China. She loves both dogs and cats.
Research Focus
Bingbin’s research aims to make machine learning methods more efficient and accessible. She is currently investigating how various inductive biases—arising from architecture, data usage, and training algorithms—affect training efficiency and inference cost. Her work combines theoretical analysis and scientific experiments, with a particular emphasis on deriving insights and algorithms from clean “sandbox” setups.