Hi, I'm Etash Guha

I'm a researcher at SambaNova Systems in Palo Alto, California.
I research how to use Machine Learning Theory for AI Safety. Specifically, I develop and analyze algorithms to ensure Deep Learning and Reinforcement Learning can be used in High Stakes Environments. I investigate properties such as Robustness, Uncertainty, Bias, Generalization, and more.
I am currently a Researcher at SambaNova Systems working on the reliability of Large Language Models. Most recently, I was a Research Intern under Dr. Emtiyaz Khan on the Approximate Bayesian Inference Team at RIKEN AIP in Tokyo, Japan. I was both an undergraduate student and Research Assistant at Georgia Tech where I worked with Vidya Muthukumar, Ashwin Pananjady, Jacob Abernethy, and Xiaoming Huo.
I have worked with researchers, traders, and software engineers while working at SambaNova Systems, FORT LP, and SAS.

Featured Research Publications

DataComp-LM
Pre-Print
Conformalization of Sparse Generalized Linear Models
International Conference of Machine Learning 2023
MINT-1T
Pre-Print
Generalization Bounds for Magnitude-Based Pruning via Sparse Matrix Sketching
ICLR 2024 Workshop on Bridging the Gap Between Practice and Theory in Deep Learning
Solving Robust MDPs through No-Regret Dynamics
Transactions of Machine Learning Research
Inverse Reinforcement Learning
Conference on Uncertainty in Artificial Intelligence 2024
On Accelerated Perceptrons and Beyond
International Conference of Learning Representations 2023