Quanming Yao, 姚权铭

Quanming Yao (姚权铭)

Associate Professor & Ph.D. Advisor

Department of Electronic Engineering, Tsinghua University

Also affiliated as a Ph.D. supervisor with the Zhongguancun Institute of Artificial Intelligence

Also affiliated with the State Key Laboratory of Space Network and Communications.

Also affiliated with the 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 Repository on GitHub, RedNote (小红书)

About Me

Dr. Quanming Yao is currently an associate professor in the Department of Electronic Engineering, Tsinghua University. Before that, he spent three years progressing from researcher to senior scientist at 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's degree from Huazhong University of Science and Technology (HUST).

He is a recipient of Top 30 Early Career to Watch (IEEE), the inaugural 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 an area chair for ICML, NeurIPS, and ICLR; served as Tutorial Chair for IJCAI 2025, and Program Co-chair of ADMA 2026. He also serves 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 a Young Fellow of BAAI.

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

Research Focus

Our research lies in core machine learning, especially scalable and data-efficient learning. I develop principled algorithms for learning under limited supervision, limited computation, and structured data, with applications in recommendation, knowledge graphs, scientific discovery, and large-model systems.

To get a sense of how we work, see this paper. To learn what we work on, see this survey.

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

Recruitment

Various positions (postdoctoral researchers / Ph.D. and master's students / research engineers / research assistants) are available. You can join us through:

Electrical Engineering Department of Tsinghua University
Qiuzhen College, Tsinghua University (with Dr. Yaqing Wang)
Zhongguancun Institute of Artificial Intelligence (select me as your research mentor)

You may read this guide to prepare to work with our group.

Recent News --- old ones ---

2026.07: I will serve as an Area Chair for AAAI 2027.
2026.07: Received the Third Prize in an electronic information teaching competition.
2026.06: I serve as founding chair of the IEEE CIS NNTC Task Force on "Data-Efficient Agentic Learning".
2026.06: We received new funding support from BSC for "Training Dynamics of LLMs."
2026.05: Our work on "Agentic DDI" is accepted to KDD.
2026.05: I was elected a Senior Member of ACM.
2026.05: Our work on "Dense Communications between LLMs" has been accepted to ICML.
2026.04: Our survey on "Data Efficient Agentic Learning" has been accepted to IJCAI.
2026.04: Our work on "Speeding up Mobile GUI Agent" has been accepted to IJCAI.
2026.04: Delivered a keynote at the ICLR 2026 Paper Sharing Event (hosted by 机器之心).
2026.04: Attended the MOE national conditions education seminar as a university representative.
2026.03: Gave a keynote at the "AGI-Next" workshop hosted by AI Time.
2026.03: Gave a keynote at the 1st Technical Meetup of OpenJiuwen.
2026.03: Our work on "Neural KG Reasoning" is accepted to AIJ.
2026.03: We received new funding support from Huawei for "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-bit LLMs" has been accepted to ICLR.
2026.01: We received new funding support from Huawei for "Cross-Device Agents."
2026.01: We received new funding support from BNRist for "Domain-Specific Agents."
2026.01: Our work "Searching to Modulate for Cold-Start Recommendation" has been accepted to IEEE TPAMI.