Jingfeng Wu  |  吴京风

I am a Ph.D. candidate (2019 - 2023, expected) at Johns Hopkins University, Computer Science Department. I am fortunate to be supervised by Prof. Vladimir Braverman. Previously I obtained B.S. in Mathematics (2012 - 2016) and M.S. in Applied Math (2016 - 2019) from Peking University, School of Mathematical Sciences.

Starting in fall 2023, I will be joining the Simons Institute for the Theory of Computing at UC Berkeley as a postdoc, hosted by Prof. Peter Bartlett and Prof. Bin Yu.

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My research focuses on bridging the gap between theory and practice in machine learning by developing efficient algorithms to solve real-world problems and providing a deep understanding of the underlying theoretical principles.

I am interested in algorithms, machine learning, optimization, and statistical learning theory.

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Conference Papers


Conference Reviewer

  • International Conference on Machine Learning (ICML), 2020 - 2023
  • Conference on Neural Information Processing Systems (NeurIPS), 2020 - 2023
  • International Conference on Learning Representations (ICLR), 2021 - 2023
  • International Conference on Artificial Intelligence and Statistics (AISTATS), 2021 - 2022
  • Conference on Uncertainty in Artificial Intelligence (UAI), 2023

Conference Program Committee Member

  • AAAI Conference on Artificial Intelligence (AAAI), 2021 - 2023

Journal Reviewer

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • Journal of Machine Learning Research (JMLR)
  • Transactions on Machine Learning Research (TMLR)
  • Applied Probability Journals

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