Joshua P. Gardner

Paul G. Allen School of Computer Science and Engineering
Google Artificial Intelligence Lab
The University of Washington

I am currently pursuing a PhD in computer science at the University of Washington's Paul G. Allen School of Computer Science & Engineering. I hold an M.S. in Applied Statistics and an M.S. in Information Science from the University of Michigan. I also hold a B.A. with Highest Honors in Philosophy from the University of Michigan.

Currently (2022), I am also a Student Researcher on the Magenta team at Google Brain, working on machine learning problems related to music and audio, including MT3.

My own research focuses on empirical machine learning: characterizing the conditions under which modern machine learning models succeed and fail. This includes understanding their overall performance, but also robustness to distribution shift, fairness, and privacy, with the aim of using this empirical understanding to select or design new methods that address these limitations. My other research interests include novel applications of deep learning (including music and audio); federated and collaborative learning; and reproducibility.

While my early research focused on machine learning and statistical inference applications in education, my main research focus is on core and applied machine learning.

Awards and honors for my past work include a Best Paper Award at the International Conference on Learning Analytics and Knowledge (LAK), the Margaret Mann Award, the UMSI Professional Practice Fellowship, and the William K. Frankena Prize.


I have been fortunate to be affiliated with the following conferences and journals as a reviewer or PC member.