I am a Ph.D. candidate at Stanford ICME. My current research interest lies in machine learning theory, in particular Federated Learning, Optimization and Deep Learning theory. I am fortunate to be advised by Professor Tengyu Ma. Before coming to Stanford, I graduated from Peking University with B.S. degrees in Computational Mathematics and Computer Science.

Honors & Awards

  • TOTAL Innovations Scholars Award, TOTAL S.A. (2020)
  • TOTAL Innovation Fellowship, TOTAL S.A. (2019 - 2020)
  • Stanford School of Engineering Fellowship, Stanford University (2017 - 2019)
  • Excellent Graduate Award, Peking University (2017)
  • National Scholarship, Peking University (2016)

Professional Affiliations and Activities

  • Member, Society of Industrial and Applied Mathematics (SIAM) (2018 - Present)
  • Member, Institute for Operations Research and the Management Sciences (INFORMS) (2019 - Present)
  • Member, Mathematical Optimization Society (MOS) (2019 - Present)

Education & Certifications

  • B.S., Peking University, Applied Mathematics (2017)
  • B.S., Peking University, Computer Science (2017)

Stanford Advisors

  • Tengyu Ma, Doctoral Dissertation Advisor (AC)

Work Experience

  • Course Assistant (for CME 307), Stanford University (2019 - 2020)

    Course Assistant for CME 307 / MS&E 311: Optimization


    Stanford University

All Publications

  • Federated Composite Optimization Yuan, H., Zaheer, M., Reddi, S., Meila, M., Zhang, T. JMLR-JOURNAL MACHINE LEARNING RESEARCH. 2021
  • Global Optimization with Orthogonality Constraints via Stochastic Diffusion on Manifold Journal of Scientific Computing Yuan, H., Gu, X., Lai, R., Wen, Z. 2019