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Short Biography

Jiangchao Yao is currently an assistant professor at Cooperative Medianet Innovation Center, Shanghai Jiao Tong University and a research scientist in Shanghai AI Laboratory. His research mainly focuses on trustworthy machine learning and reasoning with the applications towards AI4Science. Before taking the faculty job, he was an algorithm expert in Data Analytics and Intelligence Lab, DAMO Academy, Alibaba Group, and received the dual PhD degree in Shanghai Jiao Tong University and University of Technology Sydney in 2019. He has published more than 70 journal articles and conference papers, and contributed to one chapter to the book "Graph Neural Networks: Foundations, Frontiers, and Applications" (Springer). He has been the PC members of conferences including ICML, NeurIPS, ICLR, AAAI, IJCAI, and serve as the reviewers of TPAMI, TIP, TMLR, TNNLS, MLJ and TKDE.

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Research Interests

• Efficient Pretraining, Serving and Adaptation

• Generalized Imbalanced Learning

• Noise Robust Machine Learning

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Job Experience

• Research Scientist (June, 2022 -- Now)
  Shanghai AI Laboratory

• Tenure-Track Assistant Professor (April, 2022 -- Now)
  Cooperative Medianet Innovation Center, Shanghai Jiao Tong University

• Algorithm Expert (August, 2021 -- March, 2022)
  Data Analytics and Intelligence Lab, DAMO Academy, Alibaba Group

• Senior Engineer (August, 2019 -- August, 2021)
  Data Analytics and Intelligence Lab, DAMO Academy, Alibaba Group

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Education

• Doctor of Philosophy (September, 2019)
  Department of Electronic Engineering, Shanghai Jiao Tong University
  Supervised by Ya Zhang

• Doctor of Philosophy (September, 2019)
  Faculty of Engineering and Information Technology, University of Technology Sydney
  Supervised by Ivor W. Tsang

• Bachelor of Engineering (June, 2013)
  Elite Class, Department of Information Engineering, South China University of Technology