Genming Bai

Genming Bai is an Assistant Professor (non-tenure track) in the Department of Mathematics at the University of Michigan. He holds a Ph.D. in Applied Mathematics from The Hong Kong Polytechnic University (2023), an M.Sc. in Computational Science and Engineering (Robotics Track) from ETH Zurich (2021), and a B.Sc. in Physics from Peking University (2018). His research focuses on numerical methods for PDEs, structure-preserving algorithms, high-performance computing, quantum computing, and scientific machine learning.

Key research contributions include convergence analysis of finite element methods for geometric flows, development of energy-conserving numerical schemes for Schrödinger equations, and applications of physics-informed neural networks. His work has been recognized through awards such as the Junior Fellowship at Institut Mittag-Leffler (2025) and the HKMS Best Thesis Award (2024).

• Education:
  • Ph.D. in Applied Mathematics, The Hong Kong Polytechnic University (2022–2023)
  • M.Sc. in Computational Science and Engineering, ETH Zurich (2018–2021)
  • B.Sc. in Physics, Peking University (2014–2018)
• Awards:
  • Junior Fellowship, Institut Mittag-Leffler (2025)
  • HK PolyU Outstanding PhD Thesis Award (2024)
  • HKMS Best Thesis Award (2024)
  • Chinese Physics Olympiad Silver Medal (2013)

Bai's teaching includes courses on numerical methods and calculus at the University of Michigan and tutorials on statistical machine learning at HK PolyU. His research emphasizes both theoretical foundations and practical applications in computational mathematics and interdisciplinary fields.