Preetum Nakkiran is a postdoc at UCSD, hosted by Mikhail Belkin,
and part of the NSF/Simons Collaboration on the Theoretical Foundations of Deep Learning.
His research builds conceptual tools for understanding learning systems,
including deep learning--- using both theory and experiment as appropriate.
His past works include Deep Double Descent, the Deep Bootstrap Framework,
and Distributional Generalization.
Preetum obtained his PhD in Computer Science at Harvard,
advised by Boaz Barak and Madhu Sudan.
During his PhD, he co-founded the Harvard ML Foundations Group,
and co-ran the corresponding seminar series.
He has also worked with Google Research and OpenAI,
and is the prior recipient of the
Google PhD Fellowship and the NSF GRFP.
Preetum did his undergraduate work in EECS at UC Berkeley.