Researcher

Ananda Theertha Suresh

Also known as Ananda Suresh

Ananda Theertha Suresh is a machine-learning researcher whose work connects information theory, federated learning and language-model inference. He shared a 2015 NIPS Best Paper award for work on Good-Turing distribution estimation and visited the Simons Institute's Information Theory program as a graduate student. By 2017, he held a BTech from IIT Madras and a PhD in electrical and computer engineering from UC San Diego under Alon Orlitsky. He coauthored research on distributed mean estimation and SCAFFOLD for federated learning, along with a 2025 method that speeds speculative decoding by verifying token blocks together. As of October 2026, he is a research scientist at Google Research, developing algorithms for machine-learning systems with resource and privacy considerations.

Timeline

  1. 2015

    A NIPS best paper

    He shares the 2015 NIPS Best Paper award with his UC San Diego adviser Alon Orlitsky for “Competitive Distribution Estimation: Why is Good-Turing Good.”

  2. 2015

    Visiting the Simons Institute

    During spring 2015, he visits the Simons Institute's Information Theory program as a Visiting Graduate Student.

  3. By 2017

    Degrees at IIT and UCSD

    By 2017, he holds a BTech in Engineering Physics from IIT Madras and a PhD in electrical and computer engineering from UC San Diego under Alon Orlitsky.

  4. 2017

    Two research honors

    In 2017, he receives an ICML honorable mention for “A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions,” and the Marconi Society names him a Paul Baran Young Scholar.

  5. 2017

    Distributed mean estimation

    In 2017, he coauthors “Distributed Mean Estimation with Limited Communication”; a structured random rotation before quantization reduces mean-estimation error for distributed clients.

  6. 2020

    SCAFFOLD for federated learning

    In 2020, he coauthors “SCAFFOLD: Stochastic Controlled Averaging for Federated Learning,” which uses control variates to correct client drift.

  7. 2025

    Block level verification

    In 2025, he coauthors “Block level verification accelerates speculative decoding,” which verifies drafted token blocks jointly to speed large language model inference.

  8. As of October 2026

    Research scientist at Google

    As of October 2026, he is a research scientist at Google Research. He develops algorithms and theoretical formulations for machine-learning systems with resource and privacy considerations. His research spans machine learning, information theory, and statistics.

Career

  1. NowGoogle ResearchResearch Scientist
  2. 2015Simons Institute for the Theory of ComputingVisiting Graduate Student

Education

  1. IIT MadrasBTech
  2. University of California, San DiegoPhD

Sources and credits

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  1. NIPS 2015 Awards nips.cc. Checked 21 October 2026.
  2. ECE Student, Professor Win Best Paper Award at NIPS Conference today.ucsd.edu. Checked 21 October 2026.
  3. Ananda Suresh simons.berkeley.edu. Checked 21 October 2026.
  4. Marconi Society Honors Ananda Theertha Suresh with The Paul Baran Young Scholar Award - The Marconi Society marconisociety.org. Checked 21 October 2026.
  5. Ananda Theertha Suresh theertha.info. Checked 21 October 2026.
  6. Ananda Theertha Suresh, 2017 marconisociety.org. Checked 21 October 2026.
  7. ICML 2017 Awards icml.cc. Checked 21 October 2026.
  8. Distributed Mean Estimation with Limited Communication proceedings.mlr.press. Checked 21 October 2026.
  9. SCAFFOLD: Stochastic Controlled Averaging for Federated Learning proceedings.mlr.press. Checked 21 October 2026.
  10. Block level verification accelerates speculative decoding research.google. Checked 21 October 2026.
  11. Ananda Theertha Suresh research.google. Checked 21 October 2026.