Leadership
Director
Ulisses Braga-Neto
Professor
Department of Electrical and Computer Engineering
Machine learning; Statistical signal processing; Applications in engineering and science.
Steering Committee
Ulisses Braga-Neto (ECE)
Nick Duffield (TAMIDS/ECE)
Narasimha Reddy (TEES/ECE)
Lab Members
Raymundo Arroyave
Professor
Department of Materials Science and Engineering
Materials Science; Numerical Methods.
Raktim Bhattacharya
Professor
Department of Aerospace Engineering
Uncertainty quantification in SciML; Convex optimization; Information fusion in manifolds;
Asynchronous algorithms for exascale computation; Applications in astrodynamics and flight mechanics.
Yalchin Efendiev
Professor
Department of Mathematics
Multiscale methods; Porous media; Model reduction; Numerical analysis; Data-driven model reduction; Uncertainty quantification.
Eduardo Gildin
Professor
Department of Petroleum Engineering
Reservoir simulation; Model order reduction.
Diego Marcondes
Visiting Post-Doctoral Researcher
Department of Electrical and Computer Engineering
Statistical Learning Theory, Mathematical Morphology, Physics-Informed Neural Networks, Operator Learning.
Lisa Perez
Associate Director
Texas A&M High Performance Research Computing
High performance computing; Quantum chemistry; Molecular dynamics; Scientific machine learning; AI/ML.
Jean Ragusa
Professor
Department of Nuclear Engineering
Scientific computing (solution techniques, algorithms); Uncertainty quantification; Model-order reduction applied to complex radiation/multiphysics problems.
Lifan Wang
Professor
Department of Physics & Astronomy
Time-domain astronomy; Astronomical site surveys; Machine learning in astronomy; Supernovae; Astronomical polarimetry; Wide-field astronomical surveys; Cosmological parameters.
Former Lab Members
Dehao Liu
Post-Doctoral Researcher
Department of Materials Science and Engineering
TAMIDS
Computational materials science; Physics-informed machine learning; Scalable versatile Bayesian optimization; Additive manufacturing.
Levi McClenny
Research Assistant
Department of Electrical Engineering
Physics-informed deep learning, Physics-explainable AI; PINNs; Materials science.
Ming Zhong
Assistant Research Scientist
TAMIDS
Numerical ODE/PDE; Modeling and simulation; PINN/PI-GP; Inverse problems; Data recovery.