(Include but not limited to)
Track 1: Computational Modeling and Numerical Methods
Computational Modeling Theory and Methods
Numerical Analysis and Numerical Simulation
Finite Element Method, Finite Difference Method and Finite Volume Method
Boundary Element Method and Meshless Method
Spectral Method and High-Precision Numerical Formulation
Multiscale Modeling and Cross-Scale Computational Methods
Stochastic Modeling and Monte Carlo Method
Model Order Reduction and Proxy Model Method
Inverse Problems and Parameter Identification
Optimization Algorithms and Computational Modeling
Computational Fluid Dynamics and Computational Solid Mechanics
Multiscale Field Coupling Modeling and Simulation
Uncertainty Quantification and Sensitivity Analysis
Machine Learning Methods in Computational Modeling
Physical Information Neural Networks and Data-Driven Modeling
High-Performance Computing and Parallel Numerical Algorithms
Development of Computational Modeling Software and Tools
Track 2: Differential Equation Theory and Applications
Ordinary Differential Equation Theory and Qualitative Analysis
Partial Differential Equation Theory and Numerical Solution Methods
Nonlinear Differential Equations and Dynamical Systems
Fractional Differential Equations and Modeling
Stochastic Differential Equations and Stochastic Analysis
Functional Differential Equations and Delay Differential Equations
Stability and Bifurcation Theory of Differential Equations
Boundary Value Problems and Eigenvalue Problems of Differential Equations
Variational Methods and Differential Equations
Applications of Differential Equations in Physics, Biology, and Economics
Inverse Problems and Parameter Estimation of Differential Equations
Convergence and Stability of Numerical Methods for Differential Equations
Structuring Algorithms and Geometric Numerical Integration
Differential Equations and Optimal Control
Integration of Differential Equations and Machine Learning
Track 3: Applied Mathematics
Mathematical Modeling Theory and Applications
Data-Driven Modeling and Computational Methods
Mathematical Theory and Algorithms of Machine Learning
Differential Equation Methods in Deep Learning
Neural Networks and Dynamical Systems
Scientific Machine Learning and Physical Information Neural Networks
Computational Statistics and Probabilistic Modeling
Operations Research and Optimization Theory
Control Theory and Automation
Mathematical Physics and Mathematical Chemistry
Mathematical Finance and Risk Management
Biological Mathematics and Epidemic Modeling
Mathematical Methods in Image Processing
......