I have finally met Gilbert Strang who gave the NENAD plenary talk and have influenced applied and computational mathematicians in many ways.
The North America High-Order Method Conference (NAHOMCon’24) and the New England Numerical Analysis Day (NENAD ‘24) I am co-organizing with Anne Gelb and Yanlai Chen started today. There are more than 110 registered people, 18 parallel sesssions, and 20 poster presentations, which will be delivered in the next three days (including today). The program schedule can be found on the conference webpage https://math.dartmouth.edu/~nahomcon2024/.
I gave a talk entitled Stochastic Approach for Elliptic Problems in Perforated Domains in the minisymposium “MS69 Surface reconstruction: PDEs, Variational, and Deep Learning Methods - Part II of II” at SIAM Conference on Imaging Science (May 28-31, 2024, Atlanta, GA, USA).
The joint work with J. Han “A stochastic approach for elliptic problems in perforated domains” has been submitted for publication in Journal of Computational Physics. You can also check the preprint of the work at arXiv.
I presented my work with Dr. Han at the applied Mathematics colloquium at Columbia University.
I gave a talk about my work at the Mathematics of Machine Learning seminar, University of Massachusetts Amherst.
The joint work Learning the dynamics for unknown hyperbolic conservation laws using deep neural networks with Z. Chen (Exxon Mobil) and A. Gelb (Dartmouth Math) is now published in SIAM Journal on Scientific Computing. The paper was accepted back in November 28, 2023.
The joint work with T. Li and A. Gelb “A Structurally Informed Data Assimilation Approach for Nonlinear Partial Differential Equations” has been submitted for publication in Journal of Computational Physics. You can also check the preprint of the work at arXiv.
The joint work with B. Choi and J. Han “Weighted inhomogeneous regularization for inverse problems with indirect and incomplete measurement data” has been submitted for publication in International Journal of Applied and Computational Mathematics. You can also check the preprint of the work at arXiv.
I am co-organizing North America High-Order Method Conference (NAHOMCon’24) with Anne Gelb (Dartmouth College) and Yanlai Chen (UMass Dartmouth), which will be held at Dartmouth College June 17 - 19, 2024. We also organize New England Numerical Analysis Day ‘24 on June 18, 2024.
The joint work with J. Han and A. Gelb “Learning In-between Imagery Dynamics via Physical Latent Spaces” has been submitted for publication in SIAM Journal on Scientific Computing. You can also check the preprint of the work at arXiv.
The joint work with J. Han “An analysis of the derivative-free loss method for solving PDEs” has been submitted for publication in SIAM Journal on Numerical Analysis. You can also check the preprint of the work at arXiv.
I presented my joint work with Dr. Han (05598) Analysis of the derivative-free method for solving PDEs using neural networks at International Congress on Industrial and Applied Mathematics 2024, which was held at Waseda University, Tokyo, August 20-25, 2023. The talk was part of a mini-symposium [00719] Recent Advances in Numerical PDE and Scientific Machine Learning.
With T. Li (Dartmouth Math), I co-organized a mini-sympisum High Accuracy Methods for Complex Systems at International Conference on Spectral and High Order Methods 2023, which was held at Yonsei University from August 14 to 18, 2023.
I was an invited speaker at Physics-informed Machine Learning Workshop held at Posco Center, August 4, 2023.
The joint work A Bayesian Formulation for Estimating the Composition of Earth’s Crust with the Dartmouth Earth science department (G Pease, B. Keller) along with A. Gelb (Dartmouth Math) has been accepted and published in JGR Solid Earth.
The work with D. Han (Dartmouth Math) Hierarchical Learning to Solve PDEs Using Physics-Informed Neural Networks is published in Computational Science - ICCS 2023, Lecture Notes in Computer Science.
The work with D. Han (Dartmouth Math) A neural network approach for homogenization of multiscale problems is published in SIAM Multiscale Modeling and Simulation.
The joint work Improving numerical accuracy for the viscous-plastic formulation of sea ice with T. Li (Dartmouth Math) and A. Gelb (Dartmouth Math) is now published in Journal of Computational Physics.
The joint work with Dr. Han (Dartmouth Math) Inhomogeneous regularization with limited and indirect data is now published in Journal of Computational and Applied Mathematics a special issue of Computational Methods and Models in Deep Learning for inverse Problems.
I gave a talk Inhomogeneous Regularization for Ensemble Kalman Inversion in a mini-symposium “Computational Methods for Statistical Inverse Problems” at SIAM Conference on Computational Science and Engineering 2023.
On Nov 10, 2022, I presented my work with Dr. Han A Neural Network Approach for Homogenization of Multiscale Problems at the Center for Data Science and Machine Learning seminar, National University of Singapore.
I was a co-organizer of a workshop at Banff International Research Statation, New Ideas in Computational Inverse Problems (22w5118) Oct 23-28, 2022.
The work with T Li and A Gelb [1] is featured at SIAM News Blog.
With M. Parno (CRREL and Dartmouth), I organized a mini-symposium Sea Ice Modeling and Data Assimilation Part I Part II at SIAM Conference on Mathematics of Planet Earth 2022.
My Mathematical Data Science major mentee, Nandini Prasad ‘22 is on Dartmouth News. She worked on honors thesis entitled “Using Hierarchical Neural Networks to Predict Parkinson’s Disease Severity”.
With M. Choi (Postech), I organized a mini-symposium Scientific computing and machine learning at KSIAM Fall Meeting, Dec 2-5, 2021.
My work $l_p$ regularization for ensemble Kalman inversion is now published in SIAM Journal on Scientific Computing. The paper was accepted back in July 13, 2021.
I organized a mini-symposium Exploiting structures in optimization for inverse problems and learning at SIAM Conference on Computational Science and Engineering 2021, which was held at Marh 1-5, 2021.
My work Parameter estimation in the stochastic superparameterization of two-layer quasigeostrophic flows is now published in Research in the Mathematical Sciences.
I co-organized a mini-symposium Reduced-order modeling and data-driven estimation in waves and fluids at SIAM Conference on Computational Science and Engineering 2021, which was held at Marh 1-5, 2021.