Bingbin Liu
Incoming Research Fellow
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About
Bingbin Liu is a research fellow at the Kempner Institute. Her research interests lie in the mathematical and empirical science of machine learning, with a focus on self-supervised learning and language models. Before coming to Kempner, Bingbin received her PhD in Machine Learning from Carnegie Mellon University, where she was advised by Andrej Risteski and Pradeep Ravikumar. Prior to CMU, she earned an MSc degree from Stanford University and a BEng degree from the University of Hong Kong.
Research Focus
Bingbin Liu is interested in the mathematical and empirical science of machine learning phenomena. Her research uses simple abstractions as testbeds for understanding complex systems, typically beginning with theoretical analyses and subsequently applying these insights to practical scenarios. Her work has focused on understanding the design choices in self-supervised learning, as well as exploring the capabilities and limitations of Transformers in reasoning. Looking forward, she is especially interested in investigating the factors affecting training efficiency and the reliability of models at inference time.