Contributor

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.