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Biography
Biography
I am now a researcher at Ubiquant AI lab. I got my PhD in Electrical Engineering from Tsinghua University in 2023. I obtained my B.E. degree from the same department in 2017. I visited the University of Southern California in 2019.
My research interests include AI for physics, graph neural networks, spatio-temporal data mining, and time series analysis.
Email: shz13@tsinghua.org.cn
Education
Education
Ph.D., Sept. 2017 - Jan. 2023
Electronic Engineering Department, Tsinghua University, Beijing, China
Visiting Scholar and Research Assistant, Apr. 2019 - Oct. 2019
Computer Science Department, University of Southern California, Los Angeles, CA, USA
B.E., Sept. 2013 - Jul. 2017
Electronic Engineering Department, Tsinghua University, Beijing, China
Publications
Publications
AI for Physics
AI for Physics
Learning to Simulate Crowd Trajectories with Graph Networks. [pdf]
Hongzhi Shi, Quanming Yao, Yong Li.
Proceedings of the ACM Web Conference (WebConf), 2023.
Machine Learning for Spatial-temporal Data
Machine Learning for Spatial-temporal Data
Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network. [pdf]
Hongzhi Shi, Quanming Yao, Qi Guo, Yaguang Li, Lingyu Zhang, Jieping Ye, Yong Li, Yan Liu.
IEEE International Conference on Data Engineering (ICDE), 2020.
(Research track, Short paper)
Semantics-Aware Hidden Markov Model for Human Mobility.[pdf]
Hongzhi Shi, Yong Li, Hancheng Cao, Xiangxin Zhou, Chao Zhang, Vassilis Kostakos.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021. (Impact factor = 3.857)
(Shorter version got accepted by SDM, Full paper, Acceptance rate≈22.7%)
DeepDPM: Dynamic Population Mapping via Deep Neural Network.[pdf]
Zefang Zong, Jie Feng, Kechun Liu, Hongzhi Shi, Yong Li.
AAAI Conference on Artificial Intelligence (AAAI), 2019.
(Full paper, Acceptance rate≈16.2%)
Sequence Modeling
Sequence Modeling
Discovering Periodic Patterns for Large Scale Mobile Traffic Data: Method and Applications.[pdf]
Hongzhi Shi, Yong Li.
IEEE transactions on mobile computing (TMC), 2018. (Impact factor = 4.098)
A Decomposition Approach for Urban Anomaly Detection Across Spatiotemporal Data.[pdf]
Mingyang Zhang, Tong Li, Hongzhi Shi, Yong Li, Pan Hui.
International Joint Conferences on Artificial Intelligence (IJCAI), 2019.
(Full paper, Acceptance rate≈17.9%)
Big data driven mobile traffic understanding and forecasting: A time series approach.[pdf]
Fengli Xu, Yujun Lin, Jiaxin Huang, Di Wu, Hongzhi Shi, Jeungeun Song, and Yong Li.
IEEE transactions on services computing (TSC), 2016. (Impact factor = 3.520)
Working Experiences
Working Experiences
Ubiquant AI Lab | AI Researcher | Beijing Jan. 2023 – Present
Developed deep models for returns and volatility forecasting in quantitative strategies for equities and futures
4Paradigm | Machine Learning Research Intern | Beijing Nov. 2019 – June 2022
Designed graph convolutional networks for pedestrian trajectory simulation and proposed to learn graph-like rules on knowledge graphs
DiDi AI Labs | Research Intern | Beijing Nov. 2018 – Mar. 2019
Designed multi-perspective graph convolutional networks for predicting origin-destination traffic
Tencent Institute | Research Intern | Beijing Dec. 2016 – May 2017
Used Spark to analyze trajectory data and implemented trajectory prediction algorithms to achieve higher performance
China Telecom Institute | Big Data Research Intern | Beijing Jul. 2016 – Sep. 2016
Processed the large-scale cellular traffic data in Shanghai and implemented an online population estimation algorithm
Teaching Experiences
Teaching Experiences
Data and Algorithm | Instructor: Prof. Jiansheng Chen Sep. 2018 - Jan. 2019
Professional Services
Professional Services
Senior Program Committee Member: IJCAI 2021
Program Committee Member: AAAI 2020-2023, ICML 2020 (top reviewer award)-2023, IJCAI 2020, ICLR 2021-2023, ICML 2021-2023, COMPASS 2021
Invited Journal Reviewer: ACM Transactions on Intelligent Systems and Technology
Awards
Awards
ICML 2020 Top Reviewer Award 2020
National Graduate Student Scholarship of China 2019
KDD 2019 Student Travel Award 2019
Mathematical Contest in Modeling: Honorable Mention 2016
Technological Innovation Excellence Scholarship 2015 & 2016
China Undergraduate Physics Competition: First Prize Nationwide 2014
Academic Excellence Scholarship 2014
Silver Medal, Chinese Physics Olympiad 2012
Skills
Skills
Programming Languages: Python, Java, C, C++, MATLAB
Big Data Platform Tools: Spark, Hadoop
Deep Learning Tools: Pytorch, Keras, TensorFlow
Other Tools: Git, Latex, Vim, Linux, MS Offices
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