News
- 04/2022: Our draft A Numerical Algorithm for Inverse Problem from Partial Boundary Measurement Arising from Mean Field Game Problem is out. Thanks for Yat Tin Chow, Siting Liu, Levon Nurbekyan, and Stan Osher for the collaboration.
- 02/2022: Our draft Random Features for High-Dimensional Nonlocal Mean-Field Games is out. Thanks to Sudhanshu Agrawal, Wonjun Lee, and Levon Nurbekyan for the collaboration.
- 02/2022: Our draft Global Solutions to Nonconvex Problems by Evolution of Hamilton-Jacobi PDEs is out. Thanks to Howard Heaton and Stan Osher for the collaboration.
- 02/2022: I have been awarded the MGB-SIAM Early Career Fellowship.
- 02/2022: Our draft on A Neural Network Approach for Real-Time High-Dimensional Optimal Control has been accepted by IEEE Transactions on Control Systems Technology. Thanks to Derek Onken, Levon Nurbekyan, Xingjian Li, Lars Ruthotto, and Stan Osher for the collaboration.
- 12/2021: Our draft JFB: Jacobian-Free Backpropagation for Implicit Networks has been accepted by the 36th AAAI Conference on Artificial Intelligence. Thanks to Howard Heaton, Qiuwei Li, Daniel McKenzie, Stan Osher, and Wotao Yin for the collaboration. Here is a video preview
- 12/2021: I will be participating in the High Dimensional Hamilton-Jacobi PDEs Reunion Program at IPAM from Jan 5 - 21.
- 12/2021: Our draft Wasserstein-based Projections with Applications to Inverse Problems has been accepted by the SIAM Journal on Mathematics of Data Science. Thanks to Howard Heaton, Alex Lin, Stan Osher, and Wotao Yin for the collaboration.
- 12/2021: I was awarded the Open Access Mini Grant Award at Colorado School of Mines. This grant will be used to support article processing charges in future publications.
- 10/2021: Mines Applied Math and Statistics is Hiring! More information can be found here.
- 10/2021: Our Draft Fesibility-based Fixed Point Networks has been accepted by Fixed Point Theory and Algorithms for Sciences and Engineering. Thanks to Howard Heaton, Aviv Gibali, and Wotao Yin for the collaboration.
- 09/2021: Our draft Adaptive Uncertainty-Weighted ADMM for Distributed Optimization is out. Thanks to Jianping Ye and Caleb Wan for all the hard work and collaboration.
- 06/2021: Our paper PNKH-B: A Projected Newton-Krylov Method for Large-Scale Bound-Constrained Optimization has been accepted by SIAM Journal on Scientific Computing (SISC). Thanks to Kelvin Kan and Lars Ruthotto for the collaboration.
- 06/2021: Our draft Learn to Predict Equilibria via Fixed Point Networks is out. Thanks to Howard Heaton, Daniel McKenzie, Qiuwei Li, Stanley Osher, and Wotao Yin for the collaboration.
- 04/2021: Our draft Feasibility-based Fixed Point Networks is out. Thanks to Howard Heaton, Aviv Gibali, and Wotao Yin for the collaboration.
- 04/2021: Congratulations to my student Jianping Mike Ye on receiving the Undergraduate Research Fellows Program (URFP) Scholarship at UCLA! As a URFP fellow, Jianping will be developing efficient distributed optimization methods for machine learning tasks.
- 04/2021: Our preprint A Neural Network Approach for High-Dimensional Optimal Control is out. Thanks to Derek Onken, Levon Nurbekyan, Lars Ruthotto, Xingjian Li, and Stan Osher for the collaboration. Videos of our work can be found here.
- 03/2021: Our draft Fixed Point Networks: Implicit Depth Models with Jacobian-Free Backprop is out. Thanks to Howard Heaton, Qiuwei Li, Daniel McKenzie, Stanley Osher, and Wotao Yin for the collaboration. A blog of this work is available here.
- 03/2021: Our paper Alternating the Population and Agent Control Neural Networks to Solve High-Dimensional Stochastic Mean-Field Games has been accepted to PNAS. Thanks to Alex Lin, Levon Nurbekyan, Wuchen Li, and Stan Osher for the collaboration.
- 02/2021: Our paper A Neural Network Approach Applied to Multi-Agent Optimal Control has been accepted to the European Control Conference 2021 (ECC21). Thanks to Derek Onken, Levon Nurbekyan, Xingjian Li, Stan Osher, and Lars Ruthotto for the collaboration.
- 02/2021: I will be attending the Optimization under Uncertainty: Learning and Decision Making workshop at the Banff International Research Station for Mathematical Innovation and Discovery (BIRS). Thanks to Malabika Pramanik and the organizers of the workshop for the invitation.
- 01/2021: I will talk about adversarial projections for inverse problems in the PDE & Applied Math Seminar at UC Riverside. Thanks to Misha Potomkin and Weitao Chen for the invitation.
- 12/2020: Our paper OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport was accepted to AAAI Conference on Artificial Intelligence (AAAI 21). Thanks to Derek Onken, Xingjian Li, and Lars Ruthotto for the collaboration.