Lijie Chen

Lijie Chen is an Assistant Professor in the Department of Computer Science at the University of California, Berkeley. His research interests lie in theoretical computer science, with a focus on classical and quantum computational complexity theory and their connections to other fields of computer science and quantum physics. Chen received his Ph.D. in Computer Science from MIT, advised by Ryan Williams, and previously earned his bachelor's degree from Yao Class at Tsinghua University, where he worked under Prof. Jian Li on Multi-Armed Bandits. He was a Miller Postdoctoral Fellow at UC Berkeley, hosted by Avishay Tal and Umesh V. Vazirani, and visited MIT in the Spring of 2016 under the supervision of Prof. Scott Aaronson on Quantum Complexity.

Lijie Chen is an Assistant Professor at UC Berkeley, specializing in Computational Complexity, Theoretical Computer Science, and AI safety. Their research explores foundational questions in computational complexity, including the complexity-theoretic foundations of quantum supremacy experiments and hardness magnification for sparse NP languages. Chen also investigates sample complexity bounds for best arm identification and multi-armed bandit problems under matroid constraints. Additionally, they examine the theoretical limitations of multi-layer transformers and the power of statistical zero knowledge. Their work bridges theoretical computer science with practical implications for AI safety and algorithmic efficiency.