About me

I am a tenure-track Assistant Professor at the Center for Machine Learning Research and Center for Quantitative Biology at Peking University, Beijing, China.

I obtained my B.S.(2014) and Ph.D.(2019) in Computational Mathematics from School of Mathematical Sciences, Peking University, supervised by Professor Tiejun Li. I used to be a visiting graduate student in Mathematics Department, University of California, Irvine in 2018. Starting from 2012, I also served as the research assistant in the lab of Professor Fangting Li, from Center for Quantitative Biology, Peking University. My dissertation is titled Rare Event Studies in Single-Cell Systems Biology. After graduation in 2019, I started my postdoc at UC Irvine, USA under the supervision of Professor Qing Nie, and became the Visiting Assistant Professor of mathematics department from 2020 to 2023.

I joined Peking University as a faculty starting from July 2023. My research interests lie at the intersection between applied mathematics and quantitative biology. Especially I am interested in combining both the mathematical and the machine intelligence to study single-cell biological data science. I’m working on incorporating the wisdom of computational systems biology (e.g. techniques in dynamical system modeling and applied stochastic analysis) into the analysis of emergent single-cell multi-omics data with the aid of cutting-edge AI tools, toward a better understanding of cell-fate decision process across multiple temporal and spatial scales.

Specifically, my recent research interests focus on:

  • AI for Biology
    • AI-driven virtual cells: Intelligent inference and generation of cellular dynamics based on multi-omics data
    • Multi-omics foundation models and biomedical applications
  • Generative Models
    • Physics-informed generative models: Algorithmic analysis and improvements based on dynamic optimal transport, Schrödinger bridge, diffusion models, etc.
    • Applications of generative models in complex systems (e.g. climate change) and AI for Science