ABOUT ME
I am a Principal Researcher at Huawei Noah’s Ark Lab as of September 2020.
Before that I received my PhD degree from Beijing Institute of Technology with early graduation honor in 2020. From 2017 to 2020,
I was a joint training PhD student at Columbia University, New York, USA. Before getting my PhD, I already was a senior technical consultant at Santé Ventures, USA, from December 2019 to August 2020,
leading a team to develop a reinforcement learning system for financial stock investment from scratch.
My current research interests include machine learning, deep learning and reinforcement learning.
I won the Excellent Paper Award at the 2019 IEEE International Conference on Signal, Information and Data Processing.
Recent News
[July 2023] The paper entitled "Universal Domain Adaptation via Compressive Attention Matching" has been accepted by ICCV 2023.
[April 2023] The paper entitled "Generative Flow Networks for Precise Reward-Oriented Active Learning on Graphs" has been accepted by IJCAI 2023.
[April 2023] Four papers have been accepted by ICLR 2023 Tiny Paper.
[March 2023] The paper entitled "Sparse Personalized Federated Learning" has been accepted by IEEE Transactions on Neural Networks and Learning Systems.
[January 2023] I received the Best Ph.D. Thesis Award of Chinese Institute of Electronics.
[January 2023] The paper entitled "CFlowNets: Continuous Control with Generative Flow Networks" has been accepted by ICLR 2023. [Highest scoring paper in the field of GFlowNets]
[January 2023] The paper entitled "DAG Matters! GFlowNets Enhanced Explainer for Graph Neural Networks" has been accepted by ICLR 2023.
[September 2022] The paper entitled "Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again" has been accepted by NeurIPS 2022.
[May 2022] The paper entitled "S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?" has been accepted by SIGKDD 2022.
[May 2022] The paper entitled "Personalized Federated Learning via Variational Bayesian Inference" has been accepted by ICML 2022.
[February 2022] The paper entitled "Federated Learning with Position-Aware Neurons" has been accepted by CVPR 2022.
[June 2020] I received the Excellent Ph.D. Thesis Award from Beijing Institute of Technology.
[December 2019] I won the excellent paper award (TOP 5/2000+ submissions) at IEEE ICSIDP.
[December 2019] We gave an oral presentation at NeurIPS 2019 Workshop on Robust AI in Financial Services.
[August 2019] We gave an oral presentation at 2nd KDD Workshop on Anomaly Detection in Finance.
[June 2019] We gave an oral presentation at ICML 2019 Workshop on AI in Finance.
Education
Ph.D. student in Electrical Engineering, Columbia University, 2017/11 - 2020/06.
Supervisor: Prof. Xiaodong WANG.
Ph.D. student in Electronic Engineering, Beijing Institute of Technology, 2015/09 - 2020/06.
Supervisor: Prof. Zegang DING, Academician Teng LONG
and Academician Erke MAO.
Bachelor Student in Electronic Engineering, Beijing Institute of Technology, 2011/09 - 2015/06.
Services
Organizer/Area Chair (AC) of ICLR Tiny Paper Track.
Program Committee (PC) Member of ICML 2022, ECCV 2022, NeurIPS 2022, AAAI 2023, CVPR 2023, ICML 2023, ICLR 2023, ACMMM 2023, ICCV 2023, NeurIPS 2023, AAAI 2024, etc.
Journal Reviewers of IEEE TNNLS,
IEEE TSP,
IEEE TWC,
IEEE TGRS,
IEEE JSTSP,
IEEE TVT, etc.
Selected Awards
The Best Ph.D. Thesis Award of Chinese Institute of Electronics, 2022 (The highest honor of EE Ph.D. in China).
Doctoral Early Graduation Honor, 2020 (the first one in the team of Academicians Erke MAO and Teng LONG).
BIT Excellent Ph.D. Thesis, 2020.
ICSIDP Excellent Paper Award, 2019 (TOP 5/2000+ submissions).
China Scholarship Council (CSC) Scholarship, 2017.
Beijing Undergraduate Electronic Design Contest First Prize, 2014 (Top 1/800+).
ARM-CYPRESS PSoC4 Cortex-M0 Design Contest National First Prize, 2013.
