PeopleofSuperintelligence

Researcher

Krishna Pillutla

Also known as Venkata Krishna Pillutla

Krishna Pillutla is a machine-learning researcher whose work spans federated learning, text-generation evaluation, and differential privacy for large language models. After studying at IIT Bombay and Carnegie Mellon, he completed a PhD at the University of Washington in 2022 and worked as a postdoctoral researcher on user-level differential privacy at Google Research until February 2024. The MAUVE paper he coauthored introduced a divergence-frontier measure comparing model-generated and human-written text and won a NeurIPS Outstanding Paper Award in 2021, and in 2025 he coauthored the differentially private text-generation framework InvisibleInk and was named an AI2050 Early Career Fellow. Having joined IIT Madras in May 2024, he is an assistant professor and the Narayanan Family Foundation Fellow at its Wadhwani School of Data Science and AI, where his group studies privacy-preserving and robust learning and inference for LLMs and generative AI.

Timeline

  1. 2010–2015

    From IIT Bombay to Carnegie Mellon

    At IIT Bombay, he studies computer science as an undergraduate from 2010 to 2014, then defends a master's thesis in Carnegie Mellon's Computer Science Department in December 2015 with Nina Balcan as adviser.

  2. 2019–2020

    Robust aggregation and PhD fellowship

    In December 2019, he coauthors Robust Aggregation for Federated Learning, presenting an approach to keep federated learning robust when a fraction of devices send corrupted updates to the server. He also serves as a 2019–2020 J.P. Morgan PhD Fellow.

  3. 2021

    MAUVE wins a NeurIPS award

    He coauthors MAUVE in February 2021, introducing a comparison measure that evaluates text generated by a language model against human-written text using divergence frontiers. The paper receives a NeurIPS 2021 Outstanding Paper Award.

  4. 2022

    A PhD and partial personalization

    At the University of Washington's Paul G. Allen School of Computer Science & Engineering, he defends his PhD in June 2022, advised by Zaid Harchaoui and Sham Kakade. His ICML 2022 paper Federated Learning with Partial Model Personalization analyzes updating shared and personal model parameters simultaneously or alternately on devices.

  5. February 2024

    Postdoctoral work at Google Research

    In February 2024, he concludes his time as a visiting researcher (postdoc) at Google Research's Federated Learning team, where he works on user-level differential privacy.

  6. May 2024–December 2024

    Assistant professor at IIT Madras

    Joining IIT Madras in May 2024 as an assistant professor at the Wadhwani School of Data Science and AI, he focuses on privacy-preserving and robust learning and inference for LLMs and generative AI. He coauthors the November 2024 EMNLP paper User Inference Attacks on Large Language Models, which uses black-box access to an LLM and a few user samples to test for training data use, and receives a Google India Research Award in December 2024.

  7. 2025

    InvisibleInk and AI2050 fellowship

    In June 2025, he coauthors the monograph Correlated Noise Mechanisms for Differentially Private Learning on private training of AI and machine learning models, and is selected as the Narayanan Family Foundation Fellow at IIT Madras. His 2025 NeurIPS paper InvisibleInk presents a system for long-form text generation with differential privacy whose authors report an 8× or greater reduction in compute cost over state-of-the-art baselines at the same utility across privacy levels, and Schmidt Sciences names him a 2025 AI2050 Early Career Fellow.

  8. 2026

    Affiliation with aRtCS

    When the Arvind Raghunathan Center for Theoretical Computer Science at IIT Madras is officially up and running in March 2026, he is affiliated with the center. In August 2026, he coauthors The Privacy-Hallucination Tradeoff in Differentially Private Language Models, showing empirically that models pre-trained or fine-tuned with differential privacy produce more hallucinations, with increased severity under stricter privacy budgets. He is an assistant professor and the Narayanan Family Foundation Fellow at the Wadhwani School of Data Science and AI at IIT Madras in 2026, where his group studies privacy-preserving and robust learning and inference for LLMs and generative AI.

Career

  1. Until 2024Google ResearchVisiting Researcher (Postdoc)
  2. IIT MadrasAssistant Professor

Education

  1. 2022University of WashingtonPhD
  2. 2015Carnegie Mellon UniversityMaster's
  3. 2014IIT Bombay

From the biography.

  1. Google had the most people shaping AI every year from 2014 to 2025Includes Google. Our estimates of which organizations employed the most people shaping AI each year from 1955 to 2025, tracing the shift from university labs to companies.
  2. Google has the highest combined h-index among AI organizationsIncludes Google. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  3. 20% of people at companies who shape AI also hold a university role, led by Google and Stanford UniversityIncludes Google. We estimate that 539 of the 6,766 people with a known current organization (8%) hold both a university role and a company role, including 20% of people at companies and 13% of people at universities.
  4. Google alumni have founded or led 133 other organizations, more than any other AI labIncludes Google. We estimate that alumni of 17 major AI labs went on to found or lead 350 other organizations, including 226 they founded, and we trace 472 career moves directly between 23 labs since 2010.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Krishna Pillutla yet. Send us a free-licensed photo.

  1. Krishna Pillutla cs.cmu.edu. Checked 22 October 2026.
  2. [1912.13445] Robust Aggregation for Federated Learning arxiv.org. Checked 22 October 2026.
  3. About me - Krishna Pillutla krishnap25.github.io. Checked 22 October 2026.
  4. MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers arxiv.org. Checked 22 October 2026.
  5. Announcing the NeurIPS 2021 Award Recipients blog.neurips.cc. Checked 22 October 2026.
  6. Federated Learning with Partial Model Personalization proceedings.mlr.press. Checked 22 October 2026.
  7. Krishna Pillutla | Wadhwani School of Data Science and Artificial Intelligence wsai.iitm.ac.in. Checked 22 October 2026.
  8. User Inference Attacks on Large Language Models - ACL Anthology aclanthology.org. Checked 22 October 2026.
  9. [2506.08201] Correlated Noise Mechanisms for Differentially Private Learning arxiv.org. Checked 22 October 2026.
  10. [2507.02974] InvisibleInk: High-Utility and Low-Cost Text Generation with Differential Privacy arxiv.org. Checked 22 October 2026.
  11. Krishna Pillutla - AI2050 ai2050.schmidtsciences.org. Checked 22 October 2026.
  12. [2609.00492] The Privacy-Hallucination Tradeoff in Differentially Private Language Models arxiv.org. Checked 22 October 2026.