About Me

Yi Huang 

Yi Huang, Ph.D.

I am a research associate at the Computational Science Initiative of Brookhaven National Laboratory. I study deep learning and its applications to experimental physics. Specifically, I develop algorithms for data compression and noise filtering, unpaired image translations, and fusion instability prediction. Neural networks are a great alternative when first-principle methods are hard to come by and I hope that one day, we can convince physicists and other domain scientists to trust neural networks. More details of my research can be found in the Research page and my Curriculum Vitae.


  • Program Committee:

    • International Conference on Artificial Intelligence and Statistics (AISTATS), 2022, 2023

    • ACM International Conference on Multimedia (ACMMM), 2022

    • International Symposium on Artificial Intelligence and Mathematics (ISAIM), 2020

    • European Conference on Artificial Intelligence (ECAI), 2020

    • International Joint Conferences on Artificial Intelligences (IJCAI), 2020, 2021, 2022


Yi Huang
Brookhaven National Laboratory
Computational Science Initiative
Bldg. 725, Room 2-210
P.O. Box 5000
Upton, NY 11973-5000