My research interests are broadly in theoretical machine learning and statistics. Currently, I’m working to develop an improved theoretical understanding of the optimization and generalization capabilities of deep neural networks. In the past, I’ve conducted research in areas such applied probability and causal structure learning. Check out my publications page for more!
I previously received my B.S. degrees in Math and Computer Science (2020) and my M.Eng degree in EECS (2021) from MIT, where I was fortunate to be advised by Caroline Uhler. I have also collaborated with Guy Bresler, and interned at DeepMind. I am supported by the DoD NDSEG Fellowship.
In my free time I like to play ultimate frisbee and do various outdoorsy things.
You can contact me at eshnich (at) princeton (dot) edu.