Hi, I'm Etash Guha

I'm a Ph.D. student at the University of Washington Computer Science and Engineering Department.
I research how to design and improve training data curation protocols for training large text and image models. This includes synthetic data generation, data filtering, and online data sampling. I am extremely fortunate to be advised by the amazing Professors Ludwig Schmidt and Yejin Choi.
I am also 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
DataComp-LM
Conference on Neural Information Processing Systems Dataset and Benchmarks Track
Project PDF
Archon
Architecture Search Framework for LLM Inference
Submitted on 10 Dec 2024 (preprint)
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Conformal Prediction
Conformalization of Sparse Generalized Linear Models
International Conference of Machine Learning 2023
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MINT-1T
MINT-1T
Conference on Neural Information Processing Systems Dataset and Benchmarks Track
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Generalization Bounds
Generalization Bounds for Magnitude-Based Pruning via Sparse Matrix Sketching
ICLR 2024 Workshop on Bridging the Gap Between Practice and Theory in Deep Learning
Project PDF
Robust MDPs
Solving Robust MDPs through No-Regret Dynamics
Transactions of Machine Learning Research
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Inverse Reinforcement Learning
Inverse Reinforcement Learning
Conference on Uncertainty in Artificial Intelligence 2024
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Accelerated Perceptrons
On Accelerated Perceptrons and Beyond
International Conference of Learning Representations 2023
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