PeopleofSuperintelligence

Researcher

Changshui Zhang

Also known as Chang-Shui ZHANG, Chang-Shui Zhang, Chang-shui Zhang, 张长水, Zhang Changshui, ZHANG Changshui

Changshui Zhang is a Tsinghua AI researcher whose work spans few-shot learning and reasoning in large language models. He earned a mathematics BS at Peking University in 1986 and a PhD from Tsinghua's Department of Automation in 1992; he joined the department as a lecturer in 1992, became associate professor in 1995 and professor in 2000. IEEE named him a Fellow in 2018 for contributions to semi-supervised learning for signal processing, and he served on Tsinghua's Psychological and Cognitive Sciences Teaching Committee in March 2025. He coauthored a 2020 survey of few-sample learning, a 2023 arXiv study of LLM self-verification published at NAACL in 2024, and 2026 work on prompted reasoning and dynamic attention. As of October 2026, he is a professor in Tsinghua's Department of Automation and director of its Institute of Information Processing, researching deep learning, few-shot learning, causal learning and large-model reasoning.

Works
558
Citations
24,321
h-index
75
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 1986–1992

    Mathematics and an automation doctorate

    He earns a BS in mathematics at Peking University in 1986 and a PhD from Tsinghua University's Department of Automation in 1992.

  2. 1992–2000

    Tsinghua Automation faculty

    He joins Tsinghua University's Department of Automation as a lecturer in 1992, becomes associate professor in 1995, and becomes professor in 2000.

  3. 2018

    IEEE Fellow for semi-supervised learning

    The IEEE Signal Processing Society names him an IEEE Fellow in 2018 for contributions to semi-supervised learning for signal processing.

  4. 2020–2023

    A survey of few-sample learning

    In 2020, he and four coauthors post A Survey on Machine Learning from Few Samples to arXiv; it reviews 300+ papers and groups approaches as generative or discriminative. The survey is accepted by Pattern Recognition in 2023.

  5. 2023–2024

    LLM self-verification at NAACL

    In 2023, he posts A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning to arXiv; the paper is accepted to NAACL's 2024 Main Conference. The study tests how accurately models identify logical fallacies.

  6. March 2025

    Psychological sciences teaching committee

    In March 2025, he serves on Tsinghua's Teaching Committee for Psychological and Cognitive Sciences.

  7. 2026

    Prompted reasoning and dynamic attention

    In April 2026, he coauthors a survey of prompting methods for large language model reasoning, which reviews key benchmarks and reasoning methods. At ICLR 2026, he coauthors Attend to the Active, a structure-aware dynamic-attention method that identifies active subtasks during generation and suppresses attention to inactive ones.

  8. As of October 2026

    Information Processing Institute director

    As of October 2026, he is a professor in Tsinghua University's Department of Automation and director of its Institute of Information Processing. His research areas include deep learning, few-shot learning, causal learning and large-model reasoning.

Career

  1. Since 1992Tsinghua UniversityLecturer, Associate Professor
  2. 2019–2026Beijing National Research Center for Information Science and Technology
  3. 2006–2009Beijing Institute of Technology
  4. 2003–2024State Key Laboratory of Intelligent Technology and Systems

Education

  1. 1992Tsinghua UniversityPhD
  2. 1986Peking UniversityBS

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

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Tsinghua University. 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.
  2. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Tsinghua 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.
  3. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Tsinghua University. 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.
  4. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes Tsinghua 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.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Changshui Zhang yet. Send us a free-licensed photo.

  1. ZHANG Changshui-Xinya College,Tsinghua University xyc.tsinghua.edu.cn. Checked 21 October 2026.
  2. SFU cis.sfu.edu.hk. Checked 21 October 2026.
  3. 39 SPS Members Elevated to Fellow | IEEE Signal Processing Society signalprocessingsociety.org. Checked 21 October 2026.
  4. A Survey on Machine Learning from Few Samples arxiv.org. Checked 21 October 2026.
  5. A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning arxiv.org. Checked 21 October 2026.
  6. Teaching Committee-Department of Psychological and Cognitive Sciences，Tsinghua University pcs.tsinghua.edu.cn. Checked 21 October 2026.
  7. Advances in reasoning by prompting large language models: A survey sciopen.com. Checked 21 October 2026.
  8. Attend to the Active: Structure-Aware Dynamic Attention in LLMs for Compositional Instruction Following proceedings.iclr.cc. Checked 21 October 2026.
  9. 张长水 -清华大学自动化系 au.tsinghua.edu.cn. Checked 21 October 2026.
  10. ZHANG Changshui-Department of Automation. Tsinghua University au.tsinghua.edu.cn. Checked 21 October 2026.