Education

  • Columbia University, Ph.D., 2014
  • Columbia University, M.Phil., 2013
  • Columbia University, M.S., 2011
  • Hohai University, B.S.E., 2010

Work Experience

  • Associate Professor with Tenure, Renmin University of China, Beijing, 2021-present
  • Affiliate Professor, Northeastern University, Boston, MA, 2021-present
  • Assistant Professor, Northeastern University, Boston, MA, 2018-2021
  • Assistant Professor, University of Pittsburgh, Pittsburgh, PA, 2017-2018
  • Research Affiliate, MIT, Cambridge, MA, 2017-present
  • Teaching Fellow, MIT, Cambridge, MA, 2016-2017
  • Postdoctoral Associate, MIT, Cambridge, MA, 2014-2017
  • Research/Teaching Assistant, Columbia University, New York, NY, 2010-2014

RESEARCH INTERESTS

(1) mathematical and physical foundation of AI and its interdisciplinary applications
(2) interpretable machine/deep learning
(3) knowledge representation learning and reasoning
(4) physics-informed deep learning
(5) symbolic reinforcement learning and reasoning
(6) data-driven discovery of governing laws
(7) smart and resilient infrastructure.

Prospective Students/Staffs

Always having openings for undergraduate, master and doctoral students as well as postdoc researchers!!

Ph.D. Students under Prof. Sun's Supervision:
Yuan Mi, Renmin University of China (Ph.D. student, 2021-present)
Zitong Zhang, Renmin University of China (Ph.D. student, 2021-present)
Fangzheng (Andy) Sun, Northeastern University (Ph.D. student, 2019-present)
Pu Ren, Northeastern University (Ph.D. student, 2019-present)
R. Bailey Bond, Northeastern University (Ph.D. student, co-advised, 2019-present)
Chengping Rao, Northeastern University (Ph.D. student, co-advised, 2018-present)
Lele Luan, Northeastern University (Ph.D. student, 2018-present)
Zhao Chen, Northeastern University (Ph.D. student, 2017-2021; now Postdoc Associate at PNNL)

Teaching

  • Interdisciplinary Thinking and Practice of Artificial Intelligence

Research Projects

National Science Foundation (No. 2013067, $600,000), PI
National Science Foundation (No. 2125326, $1,500,000), Co-PI
National Science Foundation (No. 2053741, $400,000), Co-PI
Federal Railway Administration ($330,000), Co-PI
Association of American Railroads ($350,000), Co-PI
MathWorks Micro-grant ($25,000), PI
Northeastern University Tier-1 Project ($50,000), PI

PUBLICATIONS

2024
Learning spatiotemporal dynamics with a pretrained generative model
Zeyu Li, Wang Han, Yue Zhang, Qingfei Fu, Jingxuan Li, Lizi Qin, Ruoyu Dong, Hao Sun*, Yue Deng*, Lijun Yang*
Nature Machine Intelligence, 录用
Over-parameterized student model via tensor decomposition boosted knowledge distillation
Yu-Liang Zhan, Zhong-Yi Lu, Hao Sun*, Ze-Feng Gao*
Advances in Neural Information Processing Systems (NeurIPS‘2024)
P2C2Net: PDE-Preserved Coarse Correction Network for efficient prediction of spatiotemporal dynamics
Qi Wang, Pu Ren, Hao Zhou, Xin-Yang Liu, Zhiwen Deng, Yi Zhang, Ruizhi Chengze, Hongsheng Liu, Zidong Wang, Jian-Xun Wang, Ji-Rong Wen, Hao Sun*, Yang Liu*
Advances in Neural Information Processing Systems (NeurIPS‘2024)
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain
Pu Ren, Chengping Rao, Su Chen, Jian-Xun Wang, Hao Sun*, Yang Liu*
Computer Physics Communications, 295: 109010
Vision-based discovery of nonlinear dynamics for 3D moving target
Zitong Zhang, Yang Liu, Hao Sun*
The 32nd International Joint Conference on Artificial Intelligence (IJCAI'2024)
Reinforcement symbolic regression machine
Yilong Xu, Yang Liu, Hao Sun*
The Twelfth International Conference on Learning Representations (ICLR'2024)
2023
PhySR: Physics-informed deep super-resolution for spatiotemporal data
Pu Ren, Chengping Rao, Yang Liu, Zihan Ma, Qi Wang, Jian-Xun Wang, H Sun*
Journal of Computational Physics, 492: 112438
Encoding physics to learn reaction-diffusion processes
Chengping Rao, Pu Ren, Qi Wang, Oral Buyukozturk, Hao Sun*, Yang Liu*
Nature Machine Intelligence, 5: 765–779
Symbolic Physics Learner: Discovering governing equations via Monte Carlo tree search
Fangzheng Sun, Yang Liu, Jian-Xun Wang, Hao Sun*
The 11th International Conference on Learning Representations (ICLR'2023), Oral
2022
Towards artificial general intelligence via a multimodal foundation model
Nanyi Fei, Zhiwu Lu*, Yizhao Gao, Guoxing Yang, Yuqi Huo, Jingyuan Wen, Haoyu Lu, Ruihua Song, Xin Gao, Tao Xiang, Hao Sun*, Ji-Rong Wen*
Nature Communications, 13: 3094
Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty
Luning Sun, Daniel Zhengyu Huang, Hao Sun, Jian-Xun Wang
Advances in Neural Information Processing Systems (NeurIPS'2022)
Autoregressive matrix factorization for imputation and forecasting of spatiotemporal structural monitoring time series
Peijie Zhang, Pu Ren, Yang Liu, Hao Sun
Mechanical Systems and Signal Processing, 169, 108718
Forecasting of nonlinear dynamics based on symbolic invariance
Zhao Chen, Yang Liu, Hao Sun*
Computer Physics Communications, 277, 108382
Towards Artificial General Intelligence via a Multimodal Foundation Model
Nanyi Fei, Zhiwu Lu*, Yizhao Gao, Guoxing Yang, Yuqi Huo, Jingyuan Wen, Haoyu Lu, Ruihua Song, Xin Gao, Tao Xiang, Hao Sun*, Ji-Rong Wen*
Nature Communications, 13, 3094
Distilling Governing Laws and Source Input for Dynamical Systems from Videos
Lele Luan, Yang Liu, Hao Sun*
Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI'2022)
PhyCRNet: Physics-informed convolutional-recurrent network for solving spatiotemporal PDEs
Pu Ren, Chengping Rao, Yang Liu, Jian-Xun Wang, Hao Sun
Computer Methods in Applied Mechanics and Engineering, 389: 114399
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
Chengping Rao, Pu Ren, Yang Liu, Hao Sun*
The 10th International Conference on Learning Representations (ICLR'2022)
2021
Incremental Bayesian matrix/tensor learning for structural monitoring data imputation and response forecasting
Pu Ren, Xinyu Chen, Lijun Sun, Hao Sun*
Mechanical Systems and Signal Processing, 158, 107734
Physics-informed learning of governing equations from scarce data
Zhao Chen, Yang Liu*, Hao Sun*
Nature Communications, 12: 6136
Physics-informed Spline Learning for Nonlinear Dynamics Discovery
Fangzheng Sun, Yang Liu, Hao Sun
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI'2021), Main Track: 2054-2061.
2020
Physics-informed multi-LSTM networks for metamodeling of nonlinear structures
Ruiyang Zhang, Yang Liu, Hao Sun*
Computer Methods in Applied Mechanics and Engineering, 369: 113226

Honors and Awards

  • 2018 Forbes 30 Under 30: Science, 2018 (Citation: Hao Sun's research uses analytics and machine learning combined with internet-of-things enabled sensors to track of the health of buildings, and detect reparable damage before there's a bigger catastrophe. His team has built a prototype system, allowing them to observe ambient vibrations affecting the building and modeling its structural health.)
  • 2019 Top Ten Outstanding Chinese American Youth Award (The theme of this selection campaign is: "Inheritance and Innovation".)

Contact

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Email：haosun@ruc.edu.cn

Website：

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