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Ulisses Braga-Neto
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
Department of Materials Science and Engineering

Materials Science; Numerical Methods.

Raktim Bhattacharya
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
Department of Mathematics

Multiscale methods; Porous media; Model reduction; Numerical analysis; Data-driven model reduction; Uncertainty quantification.

Eduardo Gildin
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
Department of Nuclear Engineering

Scientific computing (solution techniques, algorithms); Uncertainty quantification; Model-order reduction applied to complex radiation/multiphysics problems.

Jian Tao
Assistant Professor
Department of Visualization

Numerical analysis; Workflow management; Data science; HPC; Scientific computation.

Lifan Wang
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

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

Numerical ODE/PDE; Modeling and simulation; PINN/PI-GP; Inverse problems; Data recovery.