Justin Whitehouse

Email: jwhiteho (at) andrew (dot) cmu (dot) edu

I am a rising fifth year PhD student in the Computer Science Department at Carnegie Mellon University. I am currently co-advised by Aaditya Ramdas and Steven Wu. On the theoretical side, I am interested in studying the growth of self-normalized processes in high or infinite-dimensional settings. Practically, I am interested in studying how self-normalized concentration can facilitate adaptive data analysis, with particular interest in applications in causal inference, online learning, and private machine learning (see papers below).

Before working in the above areas, I studied problems in stochastic scheduling and queueing with Mor Harchol-Balter and Weina Wang. In particular, we developed optimal algorithms for scheduling parallelizable jobs in multiserver systems.

Before coming to Carnegie Mellon, I was an undergraduate at Columbia University in New York City. There, I majored in mathematics and computer science. I was fortunate enough to be advised by Allison Bishop and Suman Jana .

Publications and Preprints


I have served as a teaching assistant for the following classes.