Quanming Yao (姚权铭)

Senior Scientist & Founding Leader (machine learning research team) - 4Paradigm Inc.

Tenure-track Assistant Professor & Ph.D. Advisor (incoming) - ECE Department, Tsinghua University

E-mail: qyaoaa [AT] connect.ust.hk

Github, Google Scholar, Zhihu, CV (Aug, 2020)

About Me

Dr. Quanming Yao is a senior scientist in 4Paradigm, who is also the founder and currently the leader of 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 Forbes 30 Under 30 (China), Young Scientist Awards (Hong Kong Institution of Science), Wuwen Jun Prize for Excellence Youth of Artificial Intelligenc (issued by CAAI), and a winner of Google Fellowship (in machine learning).

Group | Publications | Awards | Experience | Talks | 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: machine learning, nonconvex optimization, automated machine learning

Recent News --- old ones ---   

  • 2021.04: I was recognized as the top-3 author in WebConf 2021.
  • 2021.04: Our AutoML method (AutoSF, ICDE 2020) for KG learning ranks 1st in OGB benchmark.
  • 2021.04: Mr. Rex (Zhitao) Ying (Ph.D student at Stanford) gives us a talk on "Learning to simulate using GNN".
  • 2021.04: Dr. Hengshuang Zhao (Post-doc at Oxford) gives us a talk on "Advancing Visual Intelligence via Neural System Design".
  • 2021.04: We are hosting "Weakly-supervised Learning Special issue" on Machine Learning Journal.
  • 2021.03: We are hosting "Weakly-supervised Learning Workshop@IJCAI-2021".
  • 2021.03: Mr. Xuanyi Dong (Ph.D. student at UTS) gives us a talk on "Neural Architecture Search".
  • 2021.02: I was awarded as "Best Innovator" (4Paradigm. Inc).
  • 2021.01: Three papers on "AutoML", "knowledge graph" and "low-rank optimization", are accepted by WebConf.
  • 2020.12: I was awarded as "Young Scientist Awards" by "Hong Kong Institution of Science".
  • 2020.12: One paper on "Heterogeneous Information Networks" is accepted to TKDD.
  • 2020.11: I was selected as one of "Forbes 30 Under 30" (China).
  • 2020.11: Dr. Wenhui Yu (Ph.D., Tsinghua) gives us a talk on "Graph Convolutional Network for Collaborative Filters".
  • 2020.11: I was invited to give a talk at "之江国际青年人才论坛".
  • 2020.11: Dr. Hao Wang (assistant professor, CSE, Rutgers) gives us a talk on "Bayesian Deep Learning".
  • 2020.10: Two paper on "AutoML for Graph Neural Networks" and "AutoML for Knowledge Graph" are accepted to ICDE.
  • 2020.09: Two paper on "Robust Collaborative Filtering" and "AutoML for Knowledge Graph" are accepted to NeurIPS.
  • 2020.09: One paper on "Hyperspectral image" is accepted to TPAMI.
  • 2020.09: Dr. Ruiming Tang (Senior Researcher, Huawei Noah's Ark Lab) gives us a talk on "Recommendation System".
  • 2020.09: One paper on "Negative sampling for knowledge graph" is accepted to VLDBJ.
  • 2020.08: Dr. Bo Han (Assistant Professor, CSE, HKBU) gives us a talk on "Trustworthy Representation Learning".
  • 2020.08: I will serve as a Senior Program Committee for AAAI-2021.
  • 2020.08: I will serve as an Area Chair for IJCAI-2021.