PeopleofSuperintelligence

Researcher

Hanrui Zhang

Hanrui Zhang is a computer scientist whose research on economics and computation covers learning and decision making in the presence of strategic behavior. He studied in the Yao Class at Tsinghua University and earned a PhD in computer science at Carnegie Mellon University in 2023, advised by Vincent Conitzer, with a dissertation on machine learning algorithms that resist strategic manipulation. Along the way, his 2020 paper on prophet inequalities won the Best Student Paper award at the European Symposium on Algorithms, and Incentive-Aware PAC Learning appeared at AAAI in 2021. After a postdoctoral fellowship at SLMath, he was a visiting faculty researcher at Google Research NYC and coauthored a 2024 survey on autobidding and auctions in online advertising. He is an Assistant Professor of Computer Science and Engineering at the Chinese University of Hong Kong.

Timeline

  1. 2017

    Yao Class and barter exchange

    At Tsinghua University's Yao Class, he works closely with Wei Chen and Pingzhong Tang and wins the Outstanding Undergraduate Thesis Award. In 2017, he coauthors an AAMAS paper on barter exchange algorithms with Tang, Zhipeng Jia and Ruosong Wang.

  2. 2019

    Strategic samples at ICML

    In 2019, he coauthors "When Samples Are Strategically Selected" at ICML with Yu Cheng and Vincent Conitzer, a theoretical framework for a decision-maker who has no direct access to the samples or can inspect only a few. He also coauthors a NeurIPS 2019 paper on Q-learning with function approximation with Simon S. Du, Yuping Luo and Ruosong Wang.

  3. 2020

    Best student paper at ESA

    His 2020 paper on prophet inequalities for combinatorial welfare maximization with approximately subadditive agents wins the Best Student Paper award at the European Symposium on Algorithms. He also coauthors the NeurIPS 2020 paper "Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments" with Steven Jecmen, Ryan Liu, Nihar Shah, Vincent Conitzer and Fei Fang.

  4. 2021

    Incentive-aware PAC learning

    He and Vincent Conitzer publish "Incentive-Aware PAC Learning" at AAAI 2021, which studies PAC learning when data points modify their features to receive a better outcome. He is named a finalist for the 2021 Facebook Fellowship.

  5. 2022

    Autobidders and peer review

    In 2022, he coauthors a study of the first-price auction in the autobidding world with Yuan Deng, Jieming Mao, Vahab Mirrokni and Song Zuo, in which bidders are utility maximizers or autobidders and the seller can use machine-learned advice. His paper on reviewer splitting in two-phase paper reviewing, with Steven Jecmen, Ryan Liu, Fei Fang, Vincent Conitzer and Nihar B. Shah, receives an Honorable Mention for Best Paper at HCOMP 2022.

  6. 2023

    PhD at Carnegie Mellon

    He graduates with a PhD in Computer Science from Carnegie Mellon University in 2023, advised by Vincent Conitzer, with a dissertation on machine learning algorithms that are robust against strategic manipulation. He receives an Honorable Mention for the School of Computer Science's Distinguished Dissertation Award in 2023, then becomes a postdoctoral fellow at the Simons Laufer Mathematical Sciences Institute (SLMath, formerly MSRI), affiliated with UC Berkeley.

  7. 2024

    Autobidding at Google Research

    As a visiting faculty researcher at Google Research NYC, he works with the OMEGA Market Algorithms team led by Vahab Mirrokni. In 2024, he coauthors the survey "Auto-bidding and Auctions in Online Advertising" during his time at Google; it covers bidding algorithms, equilibrium analysis and efficiency of common auction formats, and optimal auction design.

  8. As of October 2026

    Assistant Professor at CUHK

    He is an Assistant Professor of Computer Science and Engineering at the Chinese University of Hong Kong, where his research on economics and computation covers learning and decision making in the presence of strategic behavior. He teaches Advanced Topics in Game Theory in Spring 2025 and Spring 2026 and is the local organizer and tutorial co-chair of WINE 2026.

Career

  1. NowChinese University of Hong KongAssistant Professor of Computer Science and Engineering
  2. 2024Google ResearchVisiting Faculty Researcher
  3. From 2023Simons Laufer Mathematical Sciences InstitutePostdoctoral Fellow

Education

  1. 2023Carnegie Mellon UniversityPhD in Computer Science
  2. Tsinghua University

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 Chinese University of Hong Kong. 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. Universities keep AI researchers for a median of 6 years, compared with 2 years at frontier labsIncludes Chinese University of Hong Kong. Across 15,811 dated work stays (6,529 people), median role tenure runs from 6 years at universities to 2 years at frontier labs. We compare all five organization types, starting decades from the 1970s to the 2020s, and the organizations that keep people longest.
  3. 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.
  4. 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.

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. Hanrui Zhang's Homepage hanruizha.github.io. Checked 21 October 2026.
  2. Designing and Analyzing Machine Learning Algorithms in the Presence of Strategic Behavior | HKUST CSE cse.hkust.edu.hk. Checked 21 October 2026.
  3. When Samples Are Strategically Selected proceedings.mlr.press. Checked 21 October 2026.
  4. Hanrui Zhang – CUHK CSE cse.cuhk.edu.hk. Checked 21 October 2026.
  5. Incentive-Aware PAC Learning | Proceedings of the AAAI Conference on Artificial Intelligence ojs.aaai.org. Checked 21 October 2026.
  6. [2208.10650] Efficiency of the First-Price Auction in the Autobidding World arxiv.org. Checked 21 October 2026.
  7. Hanrui Zhang | Carnegie Mellon University Computer Science Department csd.cmu.edu. Checked 21 October 2026.
  8. [2408.07685] Auto-bidding and Auctions in Online Advertising: A Survey arxiv.org. Checked 21 October 2026.