International Workshop on Multiscale Model Reduction and Scientific Machine Learning

December 4-6, 2023 · Hong Kong

Introduction

This international workshop aims to provide a forum for researchers from Hong Kong and Mainland China to exchange ideas with international experts working on Multiscale Methods and Scientific Machine Learning. It also aims to promote international collaboration on Multiscale Methods and Scientific Machine Learning, and their applications.

Organizing Committee

Invited Speakers

  • Weizhu Bao National University of Singapore
  • Daniele Boffi King Abdullah University of Science and Technology
  • Xiaochuan Cai University of Macau
  • Bjorn Engquist University of Texas at Austin
  • Helmut Harbrecht University of Basel
  • Patrick Henning Ruhr-University Bochum
  • Viet Ha Hoang Nanyang Technological University
  • Jian Huang Xiangtan University
  • Yunqing Huang Xiangtan University
  • Shi Jin Shanghai Jiaotong University
  • Axel Klawonn University of Cologne
  • Frederic Legoll Ecole Nationale des Ponts et Chaussées
  • Wing Tat Leung City University of Hong Kong
  • Guanglian Li University of Hong Kong
  • Qifeng Liao ShanghaiTech University
  • Alexei Lozinski Université de Franche-Comté
  • Ekaterina Muravleva Skoltech
  • Ivan Oseledets AIRI and Skoltech
  • Houman Owhadi Caltech
  • Daniel Peterseim University of Augsburg
  • Jianliang Qian Michigan State University
  • Robert Scheichl University of Heidelberg
  • Timo Sprekeler National University of Singapore
  • Yuhe Wang China University of Petroleum (East China)
  • Yang Xiang The Hong Kong University of Science and Technology
  • Zhiqin Xu Shanghai Jiaotong University
  • Bicheng Yan King Abdullah University of Science and Technology
  • Lei Zhang Shanghai Jiaotong Univeristy
  • Zhiwen Zhang University of Hong Kong
  • Xiang Zhou City University of Hong Kong

Registration

The registration is free, but is required for participation. To register, please fill in the following form.

Registration form

Schedule

The workshop will take place at the Yasumoto International Academic Park (YIA), Room LT2.

December 04, 2023 (Monday)

8:50-9:00 Opening remarks
9:00-9:30 Bjorn Engquist
9:35-10:05 Shi Jin
10:05-10:40 Coffee Break
10:40-11:10 Helmut Harbrecht 
11:15-11:45 Yunqing Huang
11:45-12:00 Group photo
12:00-2:00 Lunch (by invitation)
2:00-2:30 Daniele Boffi
2:35-3:05 Frederic Legoll
3:10-3:40 Robert Scheichl
3:40-4:15 Coffee Break
4:15-4:45 Lei Zhang
4:50-5:20 Zhiwen Zhang
5:25-5:55 Wing Tat Leung

December 05, 2023 (Tuesday)

9:00-9:30 Axel Klawonn
9:35-10:05 Ivan Oseledets
10:05-10:40 Coffee Break
10:40-11:10 Weizhu Bao  
11:15-11:45 Daniel Peterseim
12:00-2:00 Lunch (by invitation)
2:00-2:30 Houman Owhadi
2:35-3:05 Alexei Lozinski
3:10-3:40 Xiang Zhou
3:40-4:15 Coffee Break
4:15-4:45 Viet Ha Hoang
4:50-5:20 Ekaterina Muravleva
5:25-5:55 Yuhe Wang

December 06, 2023 (Wednesday)

9:00-9:30 Yang Xiang
9:35-10:05 Patrick Henning
10:05-10:40 Coffee Break
10:40-11:10 Xiao-Chuan Cai
11:15-11:45 Jianliang Qian
12:00-2:00 Lunch (by invitation)
2:00-2:30 Bicheng Yan 
2:35-3:05 Jian Huang
3:10-3:40 Guanglian Li
3:40-4:15 Coffee Break
4:15-4:45 Qifeng Liao
4:50-5:20 Zhiqin Xu 
5:25-5:55 Timo Sprekeler
6:30-8:30 Dinner (by invitation)

December 04, 2023 (Monday)

8:50-9:00 Opening remarks
9:00-9:30 Bjorn Engquist
Towards seamless numerical homogenization
9:35-10:05 Shi Jin
Quantum algorithms for multiscale partial differential equations
10:05-10:40 Coffee Break
10:40-11:10 Helmut Harbrecht 
Samplet based kernel matrix compression
11:15-11:45 Yunqing Huang
Physics-informed neural networks for approximating the hyperbolic PDEs
11:45-12:00 Group photo
12:00-2:00 Lunch (by invitation)
2:00-2:30 Daniele Boffi
On the numerical approximation of parameter dependent PDE eigenvalue problems: data driven models and reduced order methods
2:35-3:05 Frederic Legoll
Multiscale finite element methods for advection-diffusion problems
3:10-3:40 Robert Scheichl
Multiscale spectral generalised finite element methods
3:40-4:15 Coffee Break
4:15-4:45 Lei Zhang
Operator learning for multiscale PDEs
4:50-5:20 Zhiwen Zhang
A Filon-Clenshaw-Curtis-Smolyak rule for multi-dimensional oscillatory integrals
5:25-5:55 Wing Tat Leung
Nonlocal multicontinua model with representative volume elements

December 05, 2023 (Tuesday)

9:00-9:30 Axel Klawonn
Nonlinear FETI-DP domain decomposition methods combined with deep learning
9:35-10:05 Ivan Oseledets
Approximation of multivariate functions and operators using tensors, neural networks and neural operators
10:05-10:40 Coffee Break
10:40-11:10 Weizhu Bao  
Modeling, analysis and simulation for degenerate dipolar quantum gas
11:15-11:45 Daniel Peterseim
Superlocalized wave function approximation for the Gross-Pitaevskii equation
12:00-2:00 Lunch (by invitation)
2:00-2:30 Houman Owhadi
Computational hypergraph discovery, a Gaussian process framework for connecting the dots.
2:35-3:05 Alexei Lozinski
A non-intrusive implementation of MsFEM and some related error estimates
3:10-3:40 Xiang Zhou
Active learning of transition state on free energy surface 
3:40-4:15 Coffee Break
4:15-4:45 Viet Ha Hoang
Numerical homogenization of two scale fractional equations
4:50-5:20 Ekaterina Muravleva
Microstructure synthesis from incomplete data
5:25-5:55 Yuhe Wang
To be determined

December 06, 2023 (Wednesday)

9:00-9:30 Yang Xiang
Deep operator-splitting network (DOSnet) for solving PDEs
9:35-10:05 Patrick Henning
Finite element and multiscale approximations of superconductors
10:05-10:40 Coffee Break
10:40-11:10 Xiao-Chuan Cai
A multiscale Schwarz preconditioner for simulating blood flows in artery with aneurysm
11:15-11:45 Jianliang Qian
A fast butterfly-compressed Hadamard-Babich integrator for high-frequency Helmholtz equations in inhomogeneous media
12:00-2:00 Lunch (by invitation)
2:00-2:30 Bicheng Yan 
Coarse grid network - An efficient reduced order model for simulating multiphase flow in heterogeneous porous reservoirs
2:35-3:05 Jian Huang
Characteristic block-centered finite difference methods for Darcy-Forchheimer compressible miscible displacement problem 
3:10-3:40 Guanglian Li
Wavelet-based edge multiscale finite element methods for singularly perturbed convection-diffusion equations
3:40-4:15 Coffee Break
4:15-4:45 Qifeng Liao
A high-dimensional density estimation method and its application for domain decomposed uncertainty quantification
4:50-5:20 Zhiqin Xu 
Simple bias in deep learning
5:25-5:55 Timo Sprekeler
Homogenization of nondivergence-form PDEs with Cordes coefficients: analysis and numerical methods
6:30-8:30 Dinner (by invitation)

Special Issue

A special issue for this workshop will be published in Journal of Computational and Applied Mathematics. We invite all participants of this workshop to submit a paper. All papers will be refereed.

The deadline of submission is June 30, 2024. Instructions of submission will be announced later.

Accommodation

The following hotels are conveniently located near the CUHK campus:

Hyatt Regency Hong Kong, Sha Tin

Address
18 Chak Cheung Street, Sha Tin, New Territories, Hong Kong

Website
Click here

Directions
Click here

Royal Park Hotel

Address
8 Pak Hok Ting Street, Shatin, Hong Kong

Website
Click here

Directions
Click here

Regal Riverside Hotel

Address
34-36 Tai Chung Kiu Road, Shatin, Hong Kong

Website
Click here

Alva Hotel

Address
1 Yuen Hong Street, Shatin, Hong Kong

Website
Click here

Maps & Directions

The conference sessions will be held in the Yasumoto International Academic Park (YIA).

Please follow the route as indicated in the map below. It is a 2-5 min walk from the University Station.
You may choose either Exit A, C or D when heading to YIA.
However, please note that only Exit A or B can access to trains going towards Shatin when you are leaving the University.
Please also note that the ticket booth is located at Exit B.

Sponsors

The workshop is generously supported by the following organizations:


Department of Mathematics,
The Chinese University of Hong Kong


Faculty of Science,
The Chinese University of Hong Kong


Contact Us

For enquiries and further information, please contact:

Prof. Eric Chung

Office Phone No
(852) 3943 7972