Anish Acharya, PhD
Anish Acharya, PhD — Senior Research Scientist at Amazon Web Services

Anish Acharya

Senior Research Scientist
Amazon Web Services
Austin, Texas

About

I am a Senior Research Scientist at Amazon Web Services in Austin, Texas, working where learning theory meets agentic AI. I lead a central evaluation, red-teaming, and governance platform for agent systems, with recursive self-improvement built in so the agents keep learning and improving; it has been adopted across more than 20 AWS organizations. I received my PhD in Electrical and Computer Engineering from The University of Texas at Austin in 2025 under Inderjit S. Dhillon and Sujay Sanghavi, working on robust and efficient learning with the support of a $100,000 Meta PhD Research Grant, and along the way was a research scientist at Meta and Microsoft and Head of AI Research at Eidon AI. Before graduate school I spent three years on Amazon Alexa, moving from software engineering to applied science and shipping language understanding to Echo devices, after earlier roles as a data scientist at eBay and Schlumberger, a data engineer at FEM Inc., and a visiting researcher at the Toyota Technological Institute at Chicago. I hold an MS in EECS from UC Irvine and a BE from Jadavpur University.

Research

I study learning as a feedback process under imperfect information: what is identifiable from noisy or incomplete feedback, how to construct an objective when true utility is unobserved, and when repeated adaptation stays stable. The threads below are facets of that question, and my current work brings them together in agent systems that evaluate and modify their own behavior.

Publications

Papers

2026

2025

2024

2022

2021

2019

2014

2013

2012

2011

Granted US patents

Thesis

Robust and Efficient Learning in High Dimensions from Noisy Data

PhD, Electrical and Computer Engineering · The University of Texas at Austin, 2025
Advised by Inderjit S. Dhillon and Sujay Sanghavi. Committee: Alex Dimakis, Ludwig Schmidt, Nhat Ho.

Experience

Research experience

Education

Teaching

Academic Service