Computation & Intelligence

------ Change the world to a better place

Research Interests:

Prof. Yang is an applied analyst and a computational scientist in machine learning and scientific computing. His previous research focused on applied harmonic analysis and fast randomized algorithms for large-scale computation with applications in data processing and imaging. His recent research covers a broad range of topics bridging machine learning and scientific computing to create intelligent computing. Current projects include:

The foundation of deep learning [statement]
Machine learning-based solvers for PDEs and inverse problems [statement]
Machine learning-based reduced order modeling, system identification, and prediction [statement]
Symbolic machine learning for interpretable AI [statement]
Randomized algorithms for scientific computing and data science

Reinforcement Learning (RL):

RL for Control and Robotics

RL for Intellegent Computing

RL Theoretical Foundation

Deep Learning:

Deep Network Approximation

Deep Learning Optimization

Deep Learning Generalization

Machine Learning and PDEs

Machine Learning and Dynamical Systems

Machine Learning and Inverse Problems

Deep Learning Algorithms

Quantum Computing:

Quantum Approximation Theory

Scientific Computing:

Randomized Numerical Linear Algebra

Spectral Methods

Computational Chemistry

Computational Biology

Signal, Image, and Data Science:

Computational Data Science

Time Series Processing

Image Processing

3D Processing

Growth and Crack of Crystal

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