Quanming Yao, 姚权铭

Quanming Yao (姚权铭)

Senior Scientist & Leader (machine learning research team)

E-mail: yaoquanming [AT] 4paradigm.com or 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 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.

Recent News --- old ones ---

Open Positions: Intern and full-time opportunities for Machine Learning Research@4Paradigm . (招聘启事)
2020.09: One paper on "Hyperspectral image" is accepted by 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 by 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 by 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 by ICML.
2020.05: I give a tutorial on AutoML at deep learning course (post-graduate level) in Peking University.
2020.05: Prof. Xinggang Wang (Asso. Prof, ECE, HUST) gives us a talk on "Object detection".
2020.04: We are hosting KDD Cup 2020 AutoGraph Challenge, welcome to join and play.