PeopleofSuperintelligence

Researcher

Chicheng Zhang

Also known as 张驰丞

Chicheng Zhang is a machine learning researcher who studies how AI systems learn through interaction, from active learning to reinforcement learning and contextual bandits. He studied learning theory as an undergraduate at Peking University, earned a computer science PhD at UC San Diego in 2017, and worked in Microsoft Research NYC’s machine learning group from September 2017 to June 2019. His work spans algorithms for label-efficient learning, transfer across reinforcement learning tasks, query-efficient fairness auditing and interactive imitation learning. His paper with Tom Yan, “Active Fairness Auditing,” was an ICML 2022 Outstanding Paper Runner Up. In 2025, he received an NSF CAREER Award for interactive machine learning research with rich feedback; as of October 2026, he is an assistant professor of computer science at the University of Arizona.

Badges

Timeline

  1. 2014–2015

    Agnostic active learning

    In 2014, he and Kamalika Chaudhuri study agnostic active learning, seeking a classifier with few label queries and no assumptions about the label-generating function. Their 2015 paper “Active Learning from Weak and Strong Labelers” analyzes when a weak labeler can save queries to a strong labeler.

  2. By 2017

    Peking University and UCSD

    As an undergraduate at Peking University, he studies learning theory with Liwei Wang. He earns a computer science PhD at UC San Diego in 2017 under Kamalika Chaudhuri.

  3. September 2017–June 2019

    Postdoc at Microsoft Research

    From September 2017 to June 2019, he works as a postdoctoral researcher in the machine learning group at Microsoft Research NYC.

  4. 2021

    Multi-task reinforcement learning

    In 2021, he and Zhi Wang study multi-task reinforcement learning across similar but distinct Markov decision processes. They design a model-transfer algorithm and provide bounds on the problem’s intrinsic complexity.

  5. 2022

    Active fairness auditing

    He and Tom Yan coauthor “Active Fairness Auditing,” which proposes query-efficient algorithms to estimate demographic parity in machine-learning models. The paper earns an ICML Outstanding Paper Runner Up award in 2022.

  6. 2024

    Interactive imitation learning

    In 2024, he coauthors “Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms.” The work develops an oracle-efficient method for learning from expert demonstrations with fewer action annotations.

  7. 2025

    An NSF CAREER Award

    In 2025, he receives an NSF CAREER Award for “Foundations of Interactive Machine Learning with Rich Feedback.” The project targets data efficiency, safety and reuse of data gathered by learning systems.

  8. As of October 2026

    Assistant professor at Arizona

    As of October 2026, he is an assistant professor of computer science at the University of Arizona. His work focuses on interactive machine learning, including active learning, reinforcement learning, imitation learning and contextual bandits.

Career

  1. NowUniversity of ArizonaAssistant Professor
  2. 2017–2019Microsoft ResearchPostdoctoral Researcher

Education

  1. 2017University of California, San DiegoPhD
  2. Peking UniversityUndergraduate

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 University of Arizona. 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. Among employers with 30+ full-time cases, OpenAI leads primary technical role H-1B pay at $310,000, and Amazon, Google and Microsoft file 57% of all casesIncludes Microsoft. Across 440,669 certified US H-1B filings from 44 employers (FY2020–FY2026), OpenAI leads primary technical role base pay at $310,000 and xAI leads overall base pay at $290,000.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Arizona. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Arizona. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.

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. [1407.2657] Beyond Disagreement-based Agnostic Active Learning arxiv.org. Checked 20 October 2026.
  2. [1510.02847] Active Learning from Weak and Strong Labelers arxiv.org. Checked 20 October 2026.
  3. Chicheng Zhang 张驰丞 – Assistant Professor @ University of Arizona zcc1307.github.io. Checked 20 October 2026.
  4. Chicheng Zhang | Computer Science cs.arizona.edu. Checked 20 October 2026.
  5. [2107.08622] Provably Efficient Multi-Task Reinforcement Learning with Model Transfer arxiv.org. Checked 20 October 2026.
  6. Active fairness auditing proceedings.mlr.press. Checked 20 October 2026.
  7. ICML 2022 Awards icml.cc. Checked 20 October 2026.
  8. Agnostic Interactive Imitation Learning: New Theory and Practical Algorithms proceedings.mlr.press. Checked 20 October 2026.
  9. Chicheng Zhang receives NSF CAREER Award for advancing responsible and efficient interactive AI systems | College of Science science.arizona.edu. Checked 20 October 2026.
  10. Chicheng Zhang | UA Profiles profiles.arizona.edu. Checked 20 October 2026.