All News

(12/16/24) Gave a talk at AIMS conference 2024

I gave a talk Learning In-between Imagery Dynamics via Physical Latent Spaces at AIMS conference 2024 held at Abu Dhabi, Dec 16, 2024.

(12/09/24) Organized a session at AGU Fall Meeting 2024

I co-organized a session at AGU Fall Meeting 2024, C12B - Multiscale Observation, Modeling, and Prediction of Sea Ice Processes I Oral and C12B - Multiscale Observation, Modeling, and Prediction of Sea Ice Processes II Poster.

(12/03/24) Paper published in Physica D

The joint work with B. Choi “Sampling error mitigation through spectrum smoothing in ensemble data assimilation” has been published in Physica D.

(11/05/24) Paper submitted for publication in SISC

The joint work with L. Liu, T. Li, and A. Gelb Entropy stable conservative flux form neural networks , has been submitted for publication in SIAM Journal of Scientific Computing. This work uses entropy-stable scheme in learning conservation laws, extending my previous work with Z. Chen and A. Gelb Learning the dynamics for unknown hyperbolic conservation laws using deep neural networks.

(10/21/24) Mini-symposium and talks at SIAM MDS 2024

I organized a mini-symposium Non-intrusive Computational Methods to Incorporate Prior Knowledge for Improved Statistical Accuracy at SIAM MDS conference. Also, four of my (former and current) postdocs presented our joint work.

1. Predicting in Latent Space with Wasserstein Dependence-Maximizing Autoencoders by Keenan Eikenberry
2. DeepPropNet for Learning Non-homogeneous PDEs and Entropy-stable CFN for Hyperbolic Conservation Laws by Lizuo Liu
3. A Structurally Informed Data Assimilation Approach for Discontinuous State Variables by Tongtong Li.
4. Sampling Error Mitigation Through Spectrum Smoothing in Ensemble Data Assimilation by Bosu Choi

(10/08/24) UCAR meeting at Boulder, CO

As a Dartmouth representative, I will be visiting UCAR Oct 7-9 for its annual meeting.

(10/05/24) Paper submitted for publication in Journal of Scientific Computing

The joint work with J. Han “An analysis of the derivative-free loss method for solving PDEs” has been submitted for publication in Journal of Scientific Computing. You can also check the preprint of the work at arXiv.

(10/03/24) Numerical Methods Seminar at WPI

I presented my work with Dr. Han at the numerical methods seminar at Worcester Polytechnic Institute. Thanks Prof. Zhang for inviting me for this great opportunity to get connected with people at WPI.

(09/27/24) Paper published in SISC

The joint work with J. Han and A. Gelb “Learning In-between Imagery Dynamics via Physical Latent Spaces” is published in SIAM Journal on Scientific Computing. You can also check the preprint of the work at arXiv.

(09/17/24) Paper published in JCP

The joint work with J. Han “A stochastic approach for elliptic problems in perforated domains” has been published in Journal of Computational Physics.

(09/11/24) Lecture series at KAIST

I gave a series of lectures on Data Assimilation at KAIST hosted by Prof Hong. The lecture was intended for researchers and graduate students interested in Bayesian inference and numerical weather predictions. Topics include information theory, ensemble Kalman filters, localization, inflation, etc.

(09/10/24) Colloquium Talk at Seoul National University

I presented my work with Dr. Han at the colloquium at Seoul National University.

(09/09/24) MINDs seminar talk at Postech

I presented my work with Dr. Choi, “Sampling error mitigation through spectrum smoothing in ensemble data assimilation”, at MINDs seminar at Postech.

(09/05/24) Paper published in JCP

The joint work with T. Li and A. Gelb “A Structurally Informed Data Assimilation Approach for Nonlinear Partial Differential Equations” has been published in Journal of Computational Physics. You can also check the paper at JCP (or the preprint arXiv).

(07/25/24) Talk at WCCM 2024

I presented my work with Dr. Choi at the 16th World Congress on Computational Mechanics and 4th Pan American Congress on Computational Mechanics.

(06/18/24) Met Gilbert Strang

I have finally met Gilbert Strang who gave the NENAD plenary talk and have influenced applied and computational mathematicians in many ways.

(06/17/24) NAHOMCon'24 and NENAD '24

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/.

(05/31/24) Talks at SIAM Imaging Science Conference '24

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).

(03/21/24) Paper submitted for publication in JCP

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.

(03/19/24) Applied Mathematics Colloquium Talk at Columbia University

I presented my work with Dr. Han at the applied Mathematics colloquium at Columbia University.

(03/15/24) Talk at University of Massachusetts Amherst

I gave a talk about my work at the Mathematics of Machine Learning seminar, University of Massachusetts Amherst.

(03/06/24) Paper published in SIAM SISC

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.

(03/05/24) Paper submitted for publication in JCP

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.

(01/10/24) Paper submitted for publication in IJACM

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.

(01/03/24) Organizing conferences

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.

(10/16/23) Paper submitted for publication in SISC

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.

(08/24/23) Talk at ICIAM 2023

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.

(08/18/23) Organizing mini-symposium and talk at ICOSAHOM '23

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.

(08/04/23) Talk at PIML

I was an invited speaker at Physics-informed Machine Learning Workshop held at Posco Center, August 4, 2023.

(07/17/23) Paper published in JGR Solid Earth

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.

(07/03/23) Paper published in Lecture Notes in Computer Science

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.

(06/01/23) Paper published in SIAM MMS

The work with D. Han (Dartmouth Math) A neural network approach for homogenization of multiscale problems is published in SIAM Multiscale Modeling and Simulation.

(04/23/23) Paper published in JCP

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.

(04/23/23) Paper published in JCAM

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.

(03/03/23) Talks at CSE '23

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.

(11/10/22) Talk at National University of Singapore

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.

(10/28/22) Organizing workshop at Banff

I was a co-organizer of a workshop at Banff International Research Statation, New Ideas in Computational Inverse Problems (22w5118) Oct 23-28, 2022.

(09/08/22) My work on SIAM News blog

The work with T Li and A Gelb [1] is featured at SIAM News Blog.

(07/22/22) Organizing a minisymposium at SIAM MPE '22

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.

(06/01/22) My student on Dartmouth News

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”.

(12/05/21) Organizing a minisymposium at KSIAM Fall Meeting

With M. Choi (Postech), I organized a mini-symposium Scientific computing and machine learning at KSIAM Fall Meeting, Dec 2-5, 2021.

(09/08/21) Paper published in SISC

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.

(03/03/21) Organizing mini-symposium at CSE '21

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.

(07/02/20) Paper published in Res Math Sci

My work Parameter estimation in the stochastic superparameterization of two-layer quasigeostrophic flows is now published in Research in the Mathematical Sciences.

(07/15/19) Organizing mini-symposium at ICIAM '19

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.