Quanming Yao (姚权铭)

Tenure-track Assistant Professor & Ph.D. Advisor - Department of Electronic Engineering, Tsinghua University

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

My Photo

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), Global Top Chinese New Stars in Machine Learning (Baidu Talent Group), Forbes 30 Under 30 (China), Young Scientist Awards (Hong Kong Institution of Science), and Google Fellowship (Google AI).

He is the principal investigator of 12+ projects with a total budget of 12+ millions (RMB), which are from NSF, MOST, MoE, Tencent, Baidu, 4Paradigm, OPPO and THU. Thanks for the sponsorship.

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

Research Focus

My research focus on making machine learning faster, more compact and robust. 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, neural architecture search, few-shot learning, graph neural networks, knowledge graph

Recruitment

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 ---   

  • 2024.04: My student 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.
  • 2023.12: Our work AutoBLM (TPAMI 2023) received First Prize paper from CCF Guangdong.
  • 2023.12: Special prize for advising undergraduate research project (3 teachers in whole university).
  • 2023.12: Our paper on "Multi-Agent Reinforcement Learning" is accepted to AAAI-2024.
  • 2023.12: I will serve as an Area Chair for ICML-2024.
  • 2023.12: I was selected to give an early career talk at AAAI-2024.
  • 2023.12: I was invited to give a talk on "drug interaction prediction" at AI-TIME.
  • 2023.12: Our paper on "knowledge-driven recommendation" is accepted to ICDE-2024.
  • 2023.11: Our work on "Drug interaction prediction" has been accepted to Nat. Com (medicine).
  • 2023.11: I was invited to give a talk on "biomedical network" at RIKEN.
  • 2023.11: I will serve as an Area Chair for IJCAI-2024.
  • 2023.11: We received best student paper award from ACAIT 2023.
  • 2023.11: I was elected as a senior member of CAAI.
  • 2023.10: Our solution RelEns got the first place in OGB Leaderboards (ogbl-wikikg2/biokg).
  • 2023.10: I am among World's Top 2% Scientists (2023).
  • 2023.10: We received Tencent CCF-Rhino bird Excellent Project.
  • 2023.10: Our work on "Ensemble Learning for Knowledge Graph" has been accepted to EMNLP-2023.