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Activities
Invited Talks
[10/2023] Learning Dynamics from Sparse Data, Lawrence Berkeley National Lab.
[08/2023] Encoding Physics to Learn Reaction-Diffusion Processes, Luoyi Science.
[06/2022] Embedding Physics into Deep Learning for Spatiotemporal Systems, Lawrence Berkeley National Lab.
[03/2022] Embedding Physics into Deep Learning for Spatiotemporal Systems, Argonne National Lab.
[10/2020] Physics-Reinforced Deep Learning for Structural Metamodeling, Northeastern University.
[03/2020] Bayesian Tensor Learning for Structural Monitoring Data Imputation and Response Forecasting, Northeastern University.
Conference Presentations
[12/2023] Deep Generative Models for Earthquake Ground Motion Simulation, AGU Annual Meeting 2023.
[08/2023] Super-resolution for Scientific Data, Monterey Data Conference.
[07/2021] PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs, SIAM Annual Meeting 2021.
[05/2021] PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs, The 2021 Engineering Mechanics Institute Conference.
[05/2020] Bayesian Tensor Learning for Structural Monitoring Data Imputation and Response Forecasting, The 2020 Engineering Mechanics Institute Conference.
Services
Reviewers for Journals
Mechanical Systems and Signal Processing
Computer Methods in Applied Mechanics and Engineering
IEEE Transactions on Neural Networks and Learning Systems
IEEE Transactions on Geoscience and Remote Sensing
Theoretical and Applied Mechanics Letters
Engineering Applications of Artificial Intelligence
International Journal of Computational Fluid Dynamics
PLOS ONE
Measurement
Complex & Intelligent Systems
Teaching
[09/2021-12/2021], Structural Dynamics, Northeastern University.
[09/2022-05/2023], Capstone Project, co-advise with Dr. N. B. Erichson and Prof. M. W. Mahoney, UC Berkeley.
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