Jingfeng Wu  |  吴京风

Jingfeng Wu is an Assistant Professor of Statistics at UC Berkeley. His research focuses on deep learning theory, optimization, and statistical learning. He was a postdoctoral fellow at the Simons Institute at UC Berkeley. He earned his PhD from Johns Hopkins University, and MS and BS from Peking University.

• Assistant Professor (2026-now) of Statistics at UC Berkeley.
• Postdoc (2023-2026) at Simons Institute at UC Berkeley, hosted by Peter Bartlett and Bin Yu.
• PhD (2019-2023) in Computer Science at JHU, advised by Vova Braverman.
• BS & MS (2012-2016-2019) in Mathematics & Applied Math at Peking University.

• [12/2025] Invited talk at TTIC.
• [12/2025] Presenting a tutorial at NeurIPS 2025 with Yu-Xiang and Maryam.
• [09/2025] Invited talks at Yale, UPenn, JHU, MIT, Harvard, NYU, Columbia.
• [09/2025] Two papers accepted to NeurIPS 2025.
• [07/2025] Invited talk at the 6th Youth in High-Dimensions Conference.
• [05/2025] Invited talk at SIAM DS25.
• [05/2025] Three papers accepted to ICML 2025.
• [02/2025] Organizing a deep learning theory workshop at Simons.
• [01/2025] One paper accepted to ICLR 2025.
• [09/2024] Three papers accepted to NeurIPS 2024.
• [05/2024] One paper accepted to COLT 2024.
• [03/2024] Invited talk at UCLA CS.
• [02/2024] Invited talk at UC Berkeley Biostatistics.
• [01/2024] Two papers accepted to ICLR 2024.
• [10/2023] Selected as Rising Star in Data Science by UChicago and UCSD.
• [09/2023] Two papers accepted to NeurIPS 2023.
• [08/2023] Joining the Simons Institute at UC Berkeley as a postdoc.

• A Statistical View on Implicit Regularization: GD Dominates Ridge
  • [12/2025] TTIC, Talk at TTIC, hosted by Nati Srebro
  • [10/2025] Columbia, Machine Learning and AI Seminar, hosted by Daniel Hsu
  • [10/2025] NYU, Math and Data Seminar, hosted by Matus Telgarsky
  • [09/2025] Yale, Statistics & Data Science Seminar, hosted by Theodor Misiakiewicz, Omar Montasser
• A Statistical View on Implicit Regularization: GD for Logistic Regression
  • [07/2025] ICTP, 6th Youth in High-Dimensions Conference, hosted by Marco Mondelli et al.
  • [02/2025] UC Berkeley, Deep Learning Theory Workshop, hosted by Peter Bartlett et al.
• Reimagining Gradient Descent: Large Stepsize, Oscillation, and Acceleration
  • [10/2025] Harvard, Talk at Kempner, hosted by Sham Kakade
  • [09/2025] MIT, Talk at LIDS, hosted by Pablo Parrilo
  • [09/2025] JHU, CS Theory Seminar, hosted by Vova Braverman
  • [09/2025] UPenn, Group Seminar, hosted by Jason Altschuler
  • [06/2025] MPI & UCLA, Math Machine Learning Seminar, hosted by Guido Montufar
  • [05/2025] SIAM DS25, Dynamical Systems for Machine Learning, hosted by Molei Tao
  • [01/2025] UCLA, Level Set Meeting, hosted by Shu Liu, Stanley Osher
  • [09/2024] Simons Foundation, MoDL Annual Meeting, hosted by Peter Bartlett, Rene Vidal
  • [05/2024] UC San Diego, MoDL Collaboration Meeting, hosted by Chaoyue Liu et al.
  • [03/2024] UCLA, Computer Science Seminar, hosted by Quanquan Gu
  • [02/2024] UC Berkeley, Biostatistics Seminar, hosted by Lexin Li
  • [02/2024] UC San Diego, Group Seminar, hosted by Mikhail Belkin