Michael Celentano

About me


I am a Miller Fellow at UC Berkeley working in the Statistics Department and hosted by Martin Wainwright. I am broadly interested in problems in high-dimensional statistics. In particular, I have spent of a lot of time working on exact asymptotics, debiasing, and inference in high-dimensional models. I am also interested in the interplay between statistical estimation and computational constraints. I am currently participating as a visiting postdoc in the Computational Complexity of Statistical Inference program at the Simons Institute. I also help organize the Online Causal Inference Seminar.

Prior to the Miller Fellowship, I completed my PhD at the Stanford Statistics Department, advised by Professor Andrea Montanari and supported in part by the NSF Graduate Research Fellowship. My thesis developed new results and methods in high-dimensional linear regression using exact asymtotics and received the Theodore W. Anderson Theory of Statistics Award. In the summer of 2019, I held an internship at Microsoft Research New England, and was fortunate to be hosted by Vasilis Syrgkanis and Greg Lewis. I received a bachelor's degree in mathematics and physics in 2014 and a master's degree in electrical engineering in 2016, both from Stanford University.

Outside of statistics, I enjoy biking, hiking, and reading, and particularly enjoy political memoirs.

I am in the process of moving, and do not yet have a UC Berkeley email address. In the meantime, feel free to reach me at my previous email address mcelen (at) stanford (dot) edu.