Jingtong Su 苏敬童

Ph.D. Student, Center for Data Science, New York University Email: js12196 [@] nyu [DOT] edu

About me

Hi! I'm a Ph.D. student at NYU Center for Data Science, working with Prof. Julia Kempe on topics of machine learning. I am affiliated with the Math and Data Group and am collaborating with experts in the Center for Computational Astrophysics, Flatiron Institute. I spent a wonderful summer with Prof. Jason D. Lee and a group of incredible teammates via the Princeton ISIP program online in 2020. I obtained my Bachelor's degree in Data Science and Big Data Technology at Yuanpei College, Peking University. I did my undergraduate thesis with Prof. Yisen Wang and a group of heartwarming seniors :).

Publications

• On the Connection between Invariant Learning and Adversarial Training for Out-of-Distribution Generalization.
  Shiji Xin, Yifei Wang, Jingtong Su and Yisen Wang.
  AAAI 2023 (Oral).

• Wavelets beat Monkeys at Adversarial Robustness.
  Jingtong Su and Julia Kempe.
  NeurIPS Workshop on Machine Learning and the Physical Sciences, 2022.
  

• Adversarial Noise Injection for Learned Turbulence Simulations.
  Jingtong Su, Julia Kempe, Drummond Fielding, Nikolaos Tsilivis, Miles Cranmer, and Shirley Ho.
  NeurIPS Workshop on Machine Learning and the Physical Sciences, 2022.
  

• Can We achieve Robustness from Data Alone?
  Nikolaos Tsilivis, Jingtong Su, and Julia Kempe.
  ICML Workshop on New Frontiers in Adversarial Machine Learning, 2022.
  

• Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot.
  Jingtong Su*, Yihang Chen*, Tianle Cai*, Tianhao Wu, Ruiqi Gao, Liwei Wang and Jason D. Lee.
  NeurIPS 2020. [slides] [code]
  (* denotes equal contribution)

Selected Awards

• Outstanding Graduate in Beijing (2021)

• Merit Student Pacesetter at PKU (2019)

• Gold Medal at Chinese Physics Olympiad (2016)

• Bronze Medal at Chinese Physics Olympiad (2015)