Quanming Yao (姚权铭)

Associate Professor & Ph.D Advisor

Department of Electronic Engineering, Tsinghua University

also affiliate with Ph.D. Supervisor, Zhongguancun Institute of Artificial Intelligence

also affiliate with State Key laboratory of Space Network and Communications.

also affiliate with Beijing National Research Center for Information Science and Technology.

E-mail: qyaoaa [AT] connect.ust.hk / tsinghua.edu.cn

Office: 11-305 Room, Rohm Building, Tsinghua. Beijing, China, 100084 (MAP)

Group Code Repo on Github, RedNote (小红书)

My Photo

About Me

Dr. Quanming Yao currently is an associate professor at Department of Electronic Engineering, Tsinghua University. Before that, he spent three years from a researcher to a senior scientist in 4Paradigm INC, where he set up and led the company's machine learning research team. He obtained his Ph.D. degree at the Department of Computer Science and Engineering of Hong Kong University of Science and Technology (HKUST) and received his bachelor degree at HuaZhong University of Science and Technology (HUST).

He is a recipient of Top 30 early career to watch (IEEE), Inaugural winner of Intech Prize (Ant Group), Aharon Katzir Young Investigator Award (INNS), Forbes 30 Under 30 (China), and Google Fellowship (Google AI). He was invited to give early career talks at AAAI and IJCAI.

He regularly serves as area chairs for ICML / NeurIPS / ICLR; served as Tutorial Chair of IJCAI 2025, and Program Co-chair of ADMA 2026. He also serve as an Action Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence and a Senior Action Editor for Neural Networks. He is also a fellow of IET and young fellow of BAAI.

Finally, He mentored students to win Special Prize of Tsinghua SRT, Tsinghua Challenge Cup, National Challenge Cup and Beijing Excellent Bachelor's Thesis. He also received the EE Department's Zheng Junli Outstanding Teacher Award and Tsinghua University's Liu Bing Award.

Group | Publications | Course | Experience | Projects | Awards | Service

Research Focus

Our research focuses on generalization under limited supervision through structured context. We study how models and agentic systems can leverage relations, interaction history, task structure, and other non-label signals to achieve rapid adaptation, efficient modeling, and reliable extrapolation. Our work connects foundational questions about learning and generalization with new algorithms for scientific reasoning, language agents, and data-efficient intelligent systems.

  • To get a sense of HOW we do, you can check here. To get a sense of What we do, you can check here.

Current key words: Data-Efficient Learning · Few-shot Learning · In-context Learning · Multi-agent Systems · Scientific Machine Learning

Recruitment

Various positions (Postdoctoral Researchers / Ph.D./ Master / Research Engineers / Assistants) are avaliable. You can join us through You may read this guideline to prepare yourself with our group.

Recent News --- old ones ---   

  • 2026.04: As a representative of University to attended MOE national conditions education seminar.
  • 2026.03: Give a keynote at "AGI-Next" workshop hosted by "AI Time".
  • 2026.03: Give a keynote at the 1st Technical Meetup of OpenJiuwen.
  • 2026.03: Our work on "Neural KG Reasoning" is accepted to AIJ.
  • 2026.03: We get new funding support from Huawei on "Efficient Multi-Agent Systems".
  • 2026.03: I will be a program co-chair of ADMA.
  • 2026.01: Featured in "People Weekly"(《人民周刊》)
  • 2026.01: Our work on "pre-training of low-bits LLMs" has been accepted to ICLR.
  • 2026.01: We get new funding support from Huawei on "Cross-Device Agents".
  • 2026.01: We get new funding support from BNRist on "Domain-specific Agents".
  • 2026.01: Our work "Searching to Modulate for Cold-Start Recommendation" has been accepted to IEEE TPAMI.
  • 2025.12: Computing's Top 30 Early Career Professionals (IEEE Computer Society).
  • 2025.12: Received "Liu Bing (刘冰)" Prize from Tsinghua University.
  • 2025.12: Elected as "IET Fellow".
  • 2025.12: Received "Zheng Junli Teaching Excellence Award" (EE, Tsinghua University).
  • 2025.12: Our work on "Federated Adversarial Training" is accepted to IEEE TPAMI.
  • 2025.12: Selected as a "Zhiyuan Young Fellow" (BAAI).
  • 2025.11: Serve as an Area Chair for ICML 2026.
  • 2025.11: Got new funding support from BSC on "Industry-Specific Intelligent Agents".
  • 2025.11: Our work on "zero-shot coordination in reinforcement learning" has been accepted to AAAI 2026.
  • 2025.11: Appointment as an IEEE TPAMI Associate Editor.
  • 2025.10: Got new funding support from Huawei on "OpenPangu Project".
  • 2025.10: Excellence Prize on National Challenge Cup (Mobile GUI Agent, 2025).
  • 2025.10: Invited to be an Area Chair for ACL (Oct cicle).
  • 2025.10: I give a talk on "Evolving Topological Learning Techniques" at INNS webinar.
  • 2025.10: Our work on "Benchmarking Drug-Drug Interaction" is accepted to Bioinformatics.
  • 2025.09: Our work CBR-DDI is interviewed by MIT Tech Review (China)
  • 2025.09: Identified as World's Top 2% Scientists (by Stanford).
  • 2025.09: Our work on "Meta Contrastive Learning" is accepted to NeurIPS 2025.
  • 2025.09: Our work on "Personalized Agent" is accepted to NeurIPS 2025.