CIN-PDE 2024 Conference on Control, Inversion and Numerics for PDEs

Event: CIN-PDE 2024. Conference on Control, Inversion and Numerics for PDEs.
Date: Mon.-Thu. October 7 – 10, 2024

Next October, the Fudan University is hosting the 2nd. edition of the CIN-PDE 2024: Conference on Control, Inversion and Numerics for PDEs (CIN-PDE 2024) in collaboration with our our FAU MoD, Research Center for Mathematics of Data at FAU Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) and the Sichuan University (China), as part of the Sino-German cooperation CIN-PDE project (M-0548, 2022-2025). This project focuses on advancing research in control, inverse problems, and numerical theory of partial differential equations (PDEs).

CIN-PDE 2024 aims to share new mathematical tools and methods for systems governed by PDEs, particularly in areas such as dynamics, control, stabilization, data uncertainty, optimal control, and inverse problems, all of which are crucial to real-world applications. It will also foster in-depth collaboration between Fudan University and FAU in applied mathematical problems related to PDE analysis, enhancing the partnership within the Sino-German Mobility Program.

This event serves as a meeting point for junior and senior researchers from Germany and China, providing a unique opportunity to build new collaborations. Participants will explore a wide range of topics, including mathematical foundations of deep learning, non-locality in inverse problems, control problem solutions, numerical solutions, quantum computing for PDEs, and optimal control strategies. The latest research, core technologies, and theoretical advancements in control, inverse problems, and numerical theory related to PDEs will be discussed.

Speakers

• Jin Cheng. Fudan University
Lecture: “Runge Approximation and Learning based Numerical Methods for Lame Equations”

• Weinan E. Peking University
Lecture: “Towards an understanding of the fundamental principles behind deep learning”

• Shi Jin. Shanghai Jiao Tong University
Lecture: “Dimension liftings for quantum computation of partial differential equations and related problems”

• Günter Leugering & Yue Wang. FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg
Lecture: “Exact Boundary Controllability of a Timoshenko Beam”

• Qianxiao Li. National University of Singapore
Lecture: “Learning approximation and control”

• Yuehong Qian. Soochow University
Lecture: “Alternative Approach to Solving some Special PDEs”

• Shanjian Tang. Fudan University
Lecture: “Viscosity solution of second-order path-dependent HJB equation in Hilbert spaces”

• Gunther Uhlmann. University of Washington
Lecture: “Inverse Problems in Anisotropic Media”

• Zhiqiang Wang. Fudan University
Lecture: “Stabilization of 1-D wave equation with rational time delays”

• Pengfei Yao. Institute of Mathematics and Systems Science, CAS
Lecture: “Geometrical Rigidity of Elastic Shells”

• Xiaoming Yuan. University of Hong Kong
Lecture: “Revisiting First-order Algorithms for Optimization Problems in Industry”

• Jian Zhai. Beijing Institute of Technology
Lecture: “Inverting the Local Transverse and Mixed Ray Transforms”

• Qiong Zhang. Beijing Institute of Technology
Lecture: “Stability analysis of an abstract system with local damping”

• Ran Zhang. Jilin University
Lecture: “The weak Galerkin finite element method for elliptic eigenvalue problems”

• Shuangjian Zhang. Fudan University
Lecture: “Characterization of the Monopolist’s Profit-Maximization Problem as a Free-Boundary Problem”

• Xu Zhang. Fudan University
Lecture: “PDE Approach in Infinite-Dimensional Complex Analysis”

• Enrique Zuazua. FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg
Lecture: “Data Representation by Neural Networks: A control perspective”

Poster of the event

Schedule / Program

CIN-PDE 2024 Schedule | CIN-PDE 2024 Program

Posters session

• Clustering in Pure-attention Hardmax Transformers and Its Role in Sentiment Analysis
Albert Alcalde, Giovanni Fantuzzi, Enrique Zuazua
See poster

• Controllability of Neural Odes for Classification
Antonio Álvarez-lópez, Enrique Zuazua
See poster

• On the Geometry of Sharp Minimizers
Alberto Domínguez Corella
See poster

• Optimal Shape Design and Placement of Sensors via a Geometric Approach
Ilias Ftouhi, Enrique Zuazua
See poster

• Hybrid Parabolic-hyperbolic Effect for Heat Equations With Memory
Gengsheng Wang, Yubiao Zhang, Enrique Zuazua
See poster

• Controllability to Systems of Quasilinear Wave Equations With Fewer Controls
Long Hu, Peng Qu, Jiaxin Tong
See poster

• Nodal Control and the Turnpike Phenomenon
Martin Gugat, Rüdiger Schultz, Michael Schuster
See poster

• Multilayer Perceptrons: Multiclassification and Universal Approximation
Martín Hernández, Enrique Zuazua
See poster

• Global Entropy Solutions to Isentropic Gas Flows in General Nozzles
Peng Qu, Jiahui Wang, Zhouping Xin
See poster

• Non-uniqueness for the Compressible Euler-maxwell Equations
Shunkai Mao, Peng Qu
See poster

• Stability Analysis of Steady Transonic Flows With an External Force in a Three-dimensional Straight
Shangkun Weng, Zihao Zhang, Yan Zhou
See poster

• Fedadmm-insa: an Inexact and Self-adaptive Admm for Federated Learning
Yongcun Song, Ziqi Wang, Enrique Zuazua
See poster

WHEN

Mon.-Thu. October 7 – 10, 2024

WHERE

Fudan University, Handan Road 220, Shanghai.
Guanghua East-Main-Building 2201 (22nd Floor).
Location @GoogleMaps: Yangpu District, Shanghai, China, 200437.
会场： 复旦大学光华楼东主楼22楼 2201室，
复旦大学邯郸校区，邯郸路22号，上海。

Organizers

• Yue Wang. FAU DCN-AvH / FAU MoD, Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)
• Peng Qu. Fudan University (Shanghai, China)
• Qi Lü. Sichuan University (China)

Scientific Committee

• Enrique Zuazua. FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)
• Günter Leugering. FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany)
• Tatsien Li. Fudan University (China)
• Zhen Lei. Fudan University (China)

You might like

• CIN-PDE 2023. 1st. Edition of the Workshop on Control, Inversion and Numerics for PDEs
• CIN-PDE Project. Control, inversion and numerics for Partial Differential Equations
 
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