Gautam Goel



CMS Department
California Institute of Technology
ggoel@caltech.edu


About

I am a PhD student in the Computing and Mathematical Sciences (CMS) department at Caltech, where I am extremely fortunate to be advised by Babak Hassibi. I am broadly interested in machine learning, optimization, signal processing, and control, especially 1) online optimization and sequential decision-making under uncertainty, and 2) integrating ideas from machine learning with signal processing and control. Much of my PhD work has been supported by a National Science Foundation Graduate Research Fellowship and an Amazon AI4Science Fellowship. In 2021 I was named a Rising Star in Data Science by the University of Chicago Center for Data and Computing.

I enjoy travelling, and have visited the following countries for conferences during my PhD: Australia (CDC 2017), Sweden (COLT 2018), Japan (AISTATS 2019), and Canada (NeurIPS 2019).


Preprints

Competitive Control

with Babak Hassibi.


Publications

Regret-Optimal Full-Information Control.

with Oron Sabag, Sahin Lale, and Babak Hassibi. Appeared at ACC 2021.

Regret-optimal measurement-feedback control.

with Babak Hassibi. Appeared at L4DC 2021.

Online Optimization with Predictions and Non-convex Losses.

with Yiheng Lin and Adam Wierman. Appeared at Sigmetrics 2020.

Beyond Online Balanced Descent: An Optimal Algorithm for Smoothed Online Optimization.

with Yiheng Lin. Haoyuan Sun, and Adam Wierman. Appeared at NeurIPS 2019.

Spotlight Presentation

An Online Algorithm for Smoothed Regression and LQR control.

with Adam Wierman. Appeared at AISTATS 2019.

Smoothed Online Convex Optimization in High Dimensions via Online Balanced Descent.

with Niangjun Chen and Adam Wierman. Appeared at COLT 2018.

Thinking fast and slow: Optimization decomposition across timescales.

with Niangjun Chen and Adam Wierman. Appeared at CDC 2017.