Tomas Gonzalez

Tomas Gonzalez

ML PhD student @ CMU

I’m a PhD student in the Machine Learning Department at Carnegie Mellon University, where I am co-advised by Aaditya Ramdas and Giulia Fanti. I also co-organize the StatML group. My research is partially supported by the JPMorganChase AI PhD Fellowship.

In 2026, I interned at Google Research NYC, hosted by Monica Ribero and Travis Dick, and was a visiting graduate student in the Federated and Collaborative Learning program at the Simons Institute at UC Berkeley. Previously, I received my MSc from the Institute for Mathematical and Computational Engineering at the Catholic University of Chile, where I was advised by Cristóbal Guzmán. I was also a Student Researcher at Google Montreal, working with Courtney Paquette and Fabian Pedregosa.

Research

I’m broadly interested in the algorithmic and statistical aspects of modern machine learning. I work on problems that I find both practically relevant and intellectually challenging, with research spanning areas such as optimization and generative modeling, primarily under differential privacy constraints.

Preprints

Publications