PeopleofSuperintelligence

Researcher

Jayadev Acharya

Jayadev Acharya is an information theorist at Cornell University who studies how samples, communication, privacy and memory trade off in statistical inference and machine learning. He earned a B.Tech at IIT Kharagpur in 2007 and a Ph.D. in electrical and computer engineering at UC San Diego in 2014, then worked as a postdoctoral researcher at MIT before joining Cornell in 2016. A 2017 paper with Hirakendu Das, Alon Orlitsky and Ananda Theertha Suresh, on profile maximum likelihood for symmetric properties of distributions, won a best paper honorable mention at ICML. He received an NSF CAREER award in 2019 and a best paper award at ALT 2020, and in 2021 he coauthored the machine unlearning paper "Remember What You Want to Forget". Since 2022, he is an associate professor of electrical and computer engineering at Cornell.

Timeline

  1. 2007–2014

    A PhD at UC San Diego

    He earns a B.Tech in electronics and communication engineering at IIT Kharagpur in 2007, then an M.S. in 2009 and a Ph.D. in 2014 in electrical and computer engineering at UC San Diego, where Alon Orlitsky is his advisor. He wins the Jack Keil Wolf Student Paper Award at the International Symposium on Information Theory in 2010.

  2. 2016

    Assistant professor at Cornell

    He spends two years as a postdoctoral researcher in the Theory of Computation Group at MIT, hosted by Piotr Indyk. In August 2016, he joins Cornell as an assistant professor in the School of Electrical and Computer Engineering.

  3. 2017

    An ICML honorable mention

    With Hirakendu Das, Alon Orlitsky and Ananda Theertha Suresh, he shows that profile maximum likelihood, a single plug-in estimator, is sample competitive for all symmetric properties of discrete distributions, and asymptotically sample-optimal for support size, support coverage, entropy and proximity to uniformity. Their paper "A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions" receives a best paper honorable mention at ICML 2017.

  4. 2019

    An NSF CAREER award

    He receives a National Science Foundation CAREER award in 2019, granted through the Division of Computing and Communication Foundations. The five-year award supports his study of trade-offs among resources such as samples, time, memory, communication and privacy in data science and machine learning.

  5. 2020

    Best paper at ALT

    With Ananda Theertha Suresh, he writes "Optimal multiclass overfitting by sequence reconstruction from Hamming queries", which wins the Best Paper Award at the Algorithmic Learning Theory conference (ALT) in 2020.

  6. 2021

    Machine unlearning algorithms

    With Ayush Sekhari, Gautam Kamath and Ananda Theertha Suresh, he posts "Remember What You Want to Forget: Algorithms for Machine Unlearning" on arXiv in March 2021. The paper starts a rigorous study of generalization in machine unlearning and shows a separation between differential privacy and unlearning; it appears at NeurIPS 2021.

  7. 2022

    Associate professor at Cornell

    He is promoted to associate professor in Cornell's School of Electrical and Computer Engineering in June 2022. Cornell's College of Engineering gives him the Kenneth A. Goldman '71 Excellence in Teaching Award in 2022.

  8. 2024

    Visiting the Simons Institute

    He spends Summer 2024 as a visiting scientist in the Sublinear Algorithms program at the Simons Institute for the Theory of Computing. He is an associate professor in Electrical and Computer Engineering at Cornell University, with research interests in information theory, algorithmic statistics and machine learning.

Career

  1. Since 2016Cornell UniversityAssistant Professor, Associate Professor
  2. 2024Simons Institute for the Theory of ComputingVisiting Scientist
  3. Until 2016Massachusetts Institute of TechnologyPostdoctoral Researcher

Education

  1. 2014University of California, San DiegoPh.D.
  2. 2009University of California, San DiegoM.S.
  3. 2007Indian Institute of Technology KharagpurB.Tech

From the biography.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Jayadev Acharya. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. 11% of AI doctorate holders from 2010 to 2016 founded or led a company or lab by 10 years after graduationIncludes Cornell University. We estimate how often AI doctorate holders founded or led a company or lab by 10 years after graduation, how waiting times compare between founders and top jobs, and which universities trained the most.
  3. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes Cornell University. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Cornell University. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.

Colleagues

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

Sources and credits

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  1. jayadev acharya | Cornell Duffield Engineering ece.cornell.edu. Checked 21 October 2026.
  2. Jayadev Acharya people.ece.cornell.edu. Checked 21 October 2026.
  3. Jayadev Acharya | Simons Institute for the Theory of Computing simons.berkeley.edu. Checked 21 October 2026.
  4. ICML 2017 Awards icml.cc. Checked 21 October 2026.
  5. A Unified Maximum Likelihood Approach for Estimating Symmetric Properties of Discrete Distributions proceedings.mlr.press. Checked 21 October 2026.
  6. Six assistant professors win NSF early-career awards | Cornell Chronicle news.cornell.edu. Checked 21 October 2026.
  7. Jayadev Acharya, Indian American professor at Cornell, gets NSF award americanbazaaronline.com. Checked 21 October 2026.
  8. Remember What You Want to Forget: Algorithms for Machine Unlearning arxiv.org. Checked 21 October 2026.