I am a first year Ph.D. student in the Department of Mathematics at the University of California, Berkeley. My research interests lie in optimization, with focus on stochastic optimization and nonlinear optimization. I am interested in designing algorithms with rigorous theoretical guarantees and conducting algorithm analysis. I am also interested in applying state-of-the-art optimization algorithms to solve problems in operations research, high-dimensional statistics, machine learning and finance.

Prior to Berkeley, I received my master’s degree in Computational and Applied Mathematics from the University of Chicago, where I was advised by Prof. Mladen Kolar and Dr. Sen Na in my research. I also received supervision from Prof. Mihai Anitescu and Prof. Michael W. Mahoney on my master’s thesis and research projects. I received my bachelor’s degree in Statistics from Xiamen University, where I was advised by Prof. Yingxing Li on my undergraduate thesis.

Research Interests

• stochastic nonlinear optimization
• numerical linear algebra
• high-dimensional statistics
• statistical learning
• mathematical finance

News

• Dec. 2022: Present at Higher-Order Optimization in Machine Learning (HOOML) 2022 NeurIPS Workshop.
• Nov. 2022: A new paper Fully Stochastic Trust-Region Sequential Quadratic Programming for Equality-Constrained Optimization Problems is available on arXiv and submitted.
• Nov. 2022: Present at Computational and Applied Mathematics (CAM) Seminar at UChicago.
• Oct. 2022: Two papers are accepted by the NeurIPS Workshop Higher-Order Optimization in Machine Learning (HOOML) 2022.