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About Me (full bio)
Dr. Quanming Yao is currently the principal researcher in 4Paradigm and managing 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 winner of Google Fellowship (machine learning, 2016) and receives Ph.D. Research Excellence Award (School of Engineering, HKUST, 2018-2019).
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.
News
- Open Positions: Intern and full-time opportunities for Machine Learning Research@4Paradigm.
- 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.