Quanming Yao (姚权铭)

Assistant Professor & Ph.D Advisor

Department of Electronic Engineering, Tsinghua University

Huawei endowed professorship and ChuanXin Scholar

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

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

Github, Google Scholar, Zhihu

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About Me

Dr. Quanming Yao currently is a tenure-track assistant 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) in 2018 and received his bachelor degree at HuaZhong University of Science and Technology (HUST) in 2013.

He is a receipt of Aharon Katzir Young Investigator Award (INNS), Forbes 30 Under 30 (China), and Google Fellowship (Google AI).

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

Research Focus

My research focus on making machine learning more adaptable, compact and econmic (i.e., parsimony Learning). I wish to develop easy and intuitive methods, which can be used by many others with, perhaps, not much professional knowledge of underneath methods.

Current key words: automated machine learning, few-shot learning, meta-learning, in-context learning, knowledge graph

Please check our perspective paper: "Knowledge-Aware Parsimony Learning".


Various positions at both industry companies and Tsinghua University are avaliable.
  • Postdoctoral Researchers
  • Full-time Ph.D./ Master Program
  • Research Engineers / Assistants
Details are here: in English, in Chinese, for International Students. Please email me if you are interested in above topics.
  • For undergraduates, you may read this guideline to prepare yourself with our group.

Recent News --- old ones ---   

  • 2024.07: We got new funding support from Meituan Inc.
  • 2024.06: We got new funding support from 4Paradigm Inc.
  • 2024.06: Group member Guangyi Liu received "Excellent Graduation Thesis of Tsinghua University".
  • 2024.05: Our works on "Cold-start / Link prediction" have been accepted to KDD-2024.
  • 2024.04: We received Excellent Fund Award (Tsinghua and Tencent Joint Laboratory).
  • 2024.04: Our work on "AutoML for noisy label learning" has accepted to IEEE TPAMI.
  • 2024.04: Group member Guangyi Liu won Special prize on Tsinghua "Challenge Cup" (the only 1 in information track).
  • 2024.04: Our works on AI4Drug are on news of Tsinghua University.
  • 2024.04: Our work on "few-shot molecular property prediction" is accepted to IJCAI-2024.
  • 2024.04: I was invited to give a talk at "Huawei Computing Youth Forum".
  • 2024.04: Our perspective paper on "human-like learning from structured-data" was published in AAAI 2024.
  • 2024.03: I was invited as an Area Chair for NeurIPS-2024.
  • 2024.03: Our solution with CLGNN got 1st place on ogbn-mag.
  • 2024.02: We got new funding support from Beijing Natural Science Fund.
  • 2024.02: I was invited as an Area Chair for ACML-2024.
  • 2024.02: Our paper on "Few-Shot Molecular Property Prediction" is accepted to TPAMI.
  • 2024.02: I was elected as a Senior Member of IEEE.
  • 2024.01: Our work on Nature Computational Science is High-lighted by NFSC.
  • 2024.01: I was evaluated as one of outstanding faculty (Department of Electronic Engineering, Tsinghua University).
  • 2024.01: I was invited as a Senior Program Committee for ECAI-2024.
  • 2024.01: Two papers on knowledge graphs are accepted to ICLR-2024.
  • 2024.01: I was invited as an Area Chair for CAI-2024.
  • 2024.01: We got new funding support from Independent research program (EE, Tsinghua).
  • 2024.01: We got new funding support on "Dynamic Network Scheduling" from MOST.