Research Overview
The primary aim of the RAISE Initiative is to take a first step in building a coordination network within the Texas A&M community at the intersection among (1) foundational AI research, (2) AI for science, and (3) AI for engineering. Our current specific focuses are:
01
Foundational AI Research
Machine learning, geometric deep learning, reinforcement learning, Bayesian learning and optimization, computer vision, large language models and agents, visualization and human-AI interactions, high-performance computing and AI systems.
02
AI for Science
Quantum physics, quantum chemistry, quantum materials, density functional theory, physics informed learning and simulation, molecular simulation, dynamics, and interactions, protein modeling, drug discovery, materials discovery, mathematical modeling, and partial differential equations.
03
AI for Engineering
Fluid dynamics, aerodynamics, combustion and gas dynamics, turbulence, hypersonics, extreme environment materials, nuclear system modeling and simulation, hydraulic, subsurface, and reservoir modeling, multi-scale and multi-physics modeling.