Quanming Yao (姚权铭)

Senior Scientist & Leader (machine learning research team)

E-mail: yaoquanming [AT] 4paradigm.com or qyaoaa [AT] connect.ust.hk

4Paradigm, Hong Kong

Github, Google Scholar, Zhihu, CV (Jnl, 2019)

My Photo

About Me (full bio)

Dr. Quanming Yao is currently a senior scientist in 4Paradigm and leading the company's machine learning research group. 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 Wunwen Jun Prize of Excellence Youth of Artificial Intelligence (issued by CAAI), the runner up of Ph.D. Research Excellence Award (School of Engineering, HKUST), and a winner of Google Fellowship (in machine learning).

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.

Research Group@4Paradigm

Publications,    Awards,    Experience,    Talks,    Service,    Others


  • Open Positions: Intern and full-time opportunities for Machine Learning Research@4Paradigm.
  • 2019.12: I give an invited talk at "Young Scientist Forum @ Annual Meeting of China's Artificial Intelligence".
  • 2019.11: Our faster optimization algorithm for neural architecture search (NAS) is accepted to AAAI-2020.
  • 2019.11: We are organizing Weakly-supervised and Unsupervised Learning Workshop@SDM20, welcome to attend.
  • 2019.10: Our intern Hansi's work receives Best Paper Awards on WSL Workshop@ACML19.
  • 2019.10: I receive Wunwen Jun Prize for Excellence Youth of Artificial Intelligence (issued by CAAI).
  • 2019.10: I give an invited talk at NJUTS on AutoML for Knowledge Graph Embedding.
  • 2019.09: We are organizing AutoML competition on Weakly-supervised Learning@ACML19, welcome to play.
  • 2019.09: I will serve as a guest editor of "AutoML Special Issue on TPAMI".
  • 2019.09: We are organizing Weakly-supervised Learning Workshop@ACML19, welcome to attend.
  • 2019.08: Our paper "MPGCN" which uses GCN for the traffic prediction is accepted to ICDE-2020.
  • 2019.08: I will serve as a Senior Program Committee for AAAI-2020. Thanks for the invitation.
  • 2019.07: Assistant Prof. Yangqiu Song (CSE, HKUST) gives a talk on "Knowledge graph".
  • 2019.07: Our group receives a new member. Welcome, Dr. Huan Zhao.
  • 2019.07: Our intern Xiangning's work on collaborative filtering receives "Excellence undergraduate thesis" from Tsinghua University.
  • 2019.06: Dr. Yisen Wang gives a talk on "Adversarial Machine Learning".
  • 2019.06: Our paper on "robust semi-definite programming" is accepted to IJCAI-2019.
  • 2019.06: Our paper on "cross-organizational diabetes prediction (with a differential privacy guarantee)" is accepted to IJCAI-2019.
  • 2019.05: I received Ph.D. Research Excellence Award (1st runner) from HKUST.
  • 2019.05: Fengli Xu (Ph.D. student@Tsinghua) gives a talk on "Privacy-preserving Spatiotemporal Big Data Analytic".
  • 2019.05: Our paper "SparseHMM" modeling trajectory sequence is accepted to KDD-2019 (research track).
  • 2019.05: Our paper "AutoCross" which proposes AutoML techniques in feature engineering is accepted to KDD-2019 (industrial track).
  • 2019.05: Our paper "NORT" (studies the fundamental tensor regularization techniques) is accepted to ICML-2019.
  • 2019.03: Our paper "NGMeet" is accepted to CVPR-2019 by oral presentation; try our new model for hyper-spectral image.
  • 2019.02: Our paper "NSCaching" is accepted to ICDE-2019; try our new negative sampling method for knowledge graph embedding.