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 ---   

  • Open Positions: Intern and full-time opportunities for Machine Learning Research@4Paradigm. (招聘启事)
  • 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.
  • 2020.07: Dr. Yisen Wang (Ph.D, Tsinghua) gives us a talk on "Min-max problem in Adversarial Learning".
  • 2020.07: Mr. Xiangning Chen (Ph.D. student, UCLA) gives us a talk on "robustness in NAS".
  • 2020.07: One paper on "NAS for text recognition" is accepted to ECCV.
  • 2020.06: Mr. Weihua Hu (Ph.D. student, CSE, Stanford) gives us a talk on "Learning from Complex Relational Data".
  • 2020.06: We are holding "KDD 2020 Tutorial: Advances in Recommender Systems", welcome to attend!
  • 2020.06: Two papers on "AutoML in Noisy Label Learning" are accepted to ICML.