• As a researcher, I build and apply numerical, analytical, and machine learning tools to address complex problems in science and engineering. I am currently exploring data-driven approaches, focusing on machine learning methods for scientific discovery including AI for Science, generative AI, and large language model based techniques, and I am also exploring the possibilities of applying these methods to quantitative finance. My mathematical interests include numerical analysis, scientific computing, and mathematical physics. In the natural sciences, I am engaged with topics ranging from low-energy and high-energy physics to theoretical chemistry, materials science, and computational biology. On the engineering side, I am particularly interested in quantum and semiconductor engineering, control systems, and materials design.

• I am a PhD student in Computational Mathematics at Stanford University, working with Prof. Lexing Ying. I am also working closely with ByteDance Seed-AI for Science team. I received my PhD degree in Chemical Physics at the University of Chicago, where I worked with Prof. Yuehaw Khoo. I received my dual Bachelor’s degree in Physics and Chemistry with highest honors from the University of Chinese Academy of Sciences, where I worked with Prof. Tao Xiang and Prof. Qiang Shi.

Recent news

• The paper Approximation of High-Dimensional Gibbs Distributions with Functional Hierarchical Tensors appears in Arxiv (01/28/25)!
• The paper Solving high-dimensional Hamilton-Jacobi-Bellman equation with functional hierarchical tensor appears in Arxiv (08/10/24)!
• I started PhD program in Computational Mathematics at Stanford University (09/26/23)!
• I successfully defended my PhD in theoretical chemistry at the University of Chicago entitled “Multiscale Methods for Quantum Many-Body Systems” (08/15/23)!
• The paper Low-Rank Green’s Function Representations Applied to Dynamical Mean-Field Theory appears in PRB (06/13/23)!
• I gave a talk at the Student Computational Math Seminar, the Ohio State University on the topic of Introduction to Computational Quantum Physics (04/21/23)!
• I will be joining Stanford University as a graduate student in Computational and Mathematical Engineering this fall (04/11/23)!
• I will be attending the Modern Applied and Computational Analysis workshop at Brown University during Jun 26 - 30, 2023 (04/21/23)! Look forward to meeting you there.
• The paper Quantum Simulations of Fermionic Hamiltonians with Efficient Encoding and Ansatz Schemes has been published by Journal of Chemical Theory and Computation (2/15/23)! In this work we propose a computational protocol for quantum simulations of Fermionic Hamiltonians on a quantum computer.
• The paper Low-Rank Green’s Function Representations Applied to Dynamical Mean-Field Theory has been posted to the Arxiv (01/18/23)! In this work we show that via a low-rank decomposition, only 20-30 Matsubara frequency nodes are necessary for the Dyson equation solver of the dynamical mean-field theory, compared to 2000 which is typically used. Thanks to all of my collaborators at the Flatiron Institute, Simons Foundation!
• The paper Quantum Simulations of Fermionic Hamiltonians with Efficient Encoding and Ansatz Schemes has been posted to the Arxiv (12/04/22)! Focusing on quantum simulations of Fermionic Hamiltonians on a quantum computer, we show a substantial improvement in the scaling of circuit gate counts and a decrease in the number of required variational parameters.
• The paper Quantum Embedding Theories to Simulate Condensed Systems on Quantum Computers has been published by Nature Computational Science (7/25/22)! It is aimed at discussing different embedding theories and the perspective for their simulations on quantum computers.
• I gave an exciting talk in the APS March meeting 2022 on solving the double counting issue in quantum defect embedding theory (3/15/22)! See the slides here. I also contribute to Dr. Christian Vorwerk’s talk on the application of the embedding theory to oxides. See the slides here.
• The paper Green’s Function Formulation of Quantum Defect Embedding Theory has been published by Journal of Chemical Theory and Computation (6/1/2022)! It is aimed at solving the double counting issue in quantum defect embedding theory.
• I gave an exciting talk as the end of my experience (8/13/21)! See the slides here. I will work remotely with colleagues to finish the project.
• I just start an internship at the Flatiron Institute, working with Dr. Olivier Parcollet, Dr. Jason Kaye and Dr. Kun Chen (6/3/21).