Area of research
Statistical and Nonlinear Physics · Computational Mechanics
Research interest
Research interests include Computer science, Artificial neural network, Velocimetry, Flow (mathematics), Heat transfer, and Discretization.
Autonomous Navigation and Collision Avoidance for AGV in Dynamic Environments: An Enhanced Deep Reinforcement Learning Approach With Composite Rewards and Dynamic Update Mechanisms
Physics-Informed Neural Networks for Heat Transfer Problems
DeepM&Mnet: Inferring the electroconvection multiphysics fields based on operator approximation by neural networks
Artificial intelligence velocimetry and microaneurysm-on-a-chip for three-dimensional analysis of blood flow in physiology and disease
Forecasting solar-thermal systems performance under transient operation using a data-driven machine learning approach based on the deep operator network architecture
DeepPTV: Particle Tracking Velocimetry for Complex Flow Motion via Deep Neural Networks