PeopleofSuperintelligence

Researcher

Cho-Jui Hsieh

Also known as C. Hsieh, Cho‐Jui Hsieh

Cho-Jui Hsieh is a UCLA computer scientist who develops machine-learning methods for large-scale problems. He earned a master's degree at National Taiwan University and a PhD at the University of Texas at Austin, then moved from UC Davis to UCLA. His work includes linear classifiers that train on datasets larger than memory, research on safety in machine learning, and neural architecture search. His coauthored NAS paper won the 2021 ICLR Outstanding Paper Award, and an NSF CAREER Award supported his research on machine-learning safety. As of October 2026, he is an associate professor of computer science at UCLA.

Works
407
Citations
28,050
h-index
71
Badges

Publication numbers from OpenAlex, as of 19 October 2026.

Timeline

  1. 2009

    A master's at National Taiwan University

    At National Taiwan University, he earns a master's degree under advisor Chih-Jen Lin in 2009.

  2. 2010

    Training beyond memory

    He coauthors the 2010 KDD paper “Large Linear Classification When Data Cannot Fit in Memory,” which uses block minimization to train linear classifiers on data larger than memory. The paper wins KDD’s 2010 Best Research Paper Award.

  3. 2015

    A PhD at UT Austin

    At UT Austin, he completes a PhD in 2015 under advisor Inderjit S. Dhillon.

  4. 2018

    Joining UCLA from Davis

    In 2018, he joins UCLA Samueli after working as an assistant professor at UC Davis.

  5. 2021

    An NSF CAREER award

    In 2021, he receives an NSF CAREER Award for research that helps machine-learning models incorporate safety.

  6. 2021

    A neural architecture search award

    His coauthored paper “Rethinking Architecture Selection in Differentiable NAS” wins the ICLR 2021 Outstanding Paper Award. It proposes perturbation-based selection that measures each operation’s influence on the supernet.

  7. 2025

    Work on large language models

    In 2025, he coauthors “Large Language Models are Interpretable Learners” with Ruochen Wang, Si Si, Felix Yu, Dorothea Wiesmann, and Inderjit Dhillon; the paper appears at ICLR.

  8. As of October 2026

    Associate professor at UCLA

    As of October 2026, he is an associate professor of computer science at UCLA and develops algorithms and optimization techniques for large-scale machine learning.

Career

  1. Since 2018University of California, Los AngelesAssociate professor
  2. 2020–2023Amazon
  3. 2019–2025Google
  4. 2015–2018University of California, DavisAssistant professor

Education

  1. 2015University of Texas at AustinPhD
  2. 2009National Taiwan UniversityMaster's degree

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. LIBLINEAR: A Library for Large Linear Classification2008 · 6,578 citationsWith Chih-Jen Lin
  2. ZOO2017 · ACM Workshop on Artificial Intelligence and Security (AISec) · 1,758 citationsWith Pin-Yu Chen
  3. Cluster-GCN2019 · ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD) · 1,314 citationsWith Samy Bengio
  4. VisualBERT: A Simple and Performant Baseline for Vision and Language2019 · 1,198 citations
  5. A dual coordinate descent method for large-scale linear SVM2008 · International Conference on Machine Learning · 882 citationsWith Chih-Jen Lin

From OpenAlex, as of 19 October 2026.

  1. Google alumni founded or led 87 other organizations, the most among the labs we compareIncludes Cho-Jui Hsieh. We trace 212 organizations founded or led by AI lab alumni, and 223 career moves between the labs.
  2. Stanford University trained or employed 20 of the 89 AI major-prize winners, more than any other universityIncludes University of California, Los Angeles. Stanford University trained or employed 20 of the 89 AI major-prize winners, more than any other university. We compare doctorate and employment links for major-prize and best-paper winners.
  3. Google has the highest combined h-index among AI organizationsIncludes University of California, Los Angeles. Our estimates of combined and median h-index at AI organizations, using current affiliations and OpenAlex records.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of California, Los Angeles. Our estimates of where the people shaping AI studied and where their careers led, from education records in cited biographies.

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 Cho-Jui Hsieh yet. Send us a free-licensed photo.

  1. Statistics Seminar – Verifying and Enhancing the Robustness of Neural Networks – Cho-Jui Hsieh | CS cs.ucla.edu. Checked 19 October 2026.
  2. Large Linear Classification when Data Cannot Fit In Memory - Microsoft Research microsoft.com. Checked 19 October 2026.
  3. National Taiwan University_Hightlights100921_1 ntuweb.cloud.ntu.edu.tw. Checked 19 October 2026.
  4. UCLA Samueli hires four new CS faculty for 2018-2019 cs.ucla.edu. Checked 19 October 2026.
  5. Professor Cho-Jui Hsieh Receives NSF CAREER Award to Make Machine Learning Smarter and Safer | CS cs.ucla.edu. Checked 19 October 2026.
  6. Professor Hsieh and His Students Won the ICLR 2021 Outstanding Paper Award cs.ucla.edu. Checked 19 October 2026.
  7. [2108.04392] Rethinking Architecture Selection in Differentiable NAS arxiv.org. Checked 19 October 2026.
  8. Cho-Jui Hsieh web.cs.ucla.edu. Checked 19 October 2026.
  9. Cho-Jui Hsieh web.cs.ucla.edu. Checked 19 October 2026.