Machine Learning / Artificial Intelligence

Machine Learning / Artificial Intelligence

As the artificial intelligence and machine learning revolution permeates every aspect of our lives, materials science and engineering is no exception. In fact, at the University of Florida, we are both developing and applying AI/ML tools for the design, fabrication, and characterization of advanced materials with optimized performance.  Whether by developing and implementing high throughput genetic algorithms, deep neural networks for structure-property relationship identification and analysis, or image segmentation and generative models for microscopy, we are leading the AI/ML revolution in materials.  Examples of our current projects are presented below.

Faculty

Photo of Richard Hennig Richard HennigProfessor, Alumni Professor of Materials Science & Engineering
Work 154 Rhines Hall (352) 392-7327

Ph.D., 2000, Washington University in St. Louis

Research interests: Computational materials science, ab-initio methods, structure prediction algorithms, two-dimensional materials, materials for energy technologies, solid-liquid interfaces

Lab Website: Hennig Materials Theory Lab

Photo of Juan C. Nino Juan NinoProfessor
Work 166 Rhines Hall (352) 846-3787

Ph. D., 2002, The Pennsylvania State University

Research Interests: Multifunctional ceramics; energy materials; dielectrics and ionic conductors in bulk and thin film; single crystal growth; nuclear materials and detectors; bioceramics

Lab Website: Nino Research Group (NRG)

Photo of Michael Tonks Michael TonksProfessor and Associate Department Chair, Alumni Professor of Materials Science & Engineering
Work 158 Rhines Hall (352) 846-3779

Ph.D., 2008, University of Illinois, Urbana-Champaign

Research Interests: Computational materials science, Computational mechanics, Coevolution of microstructure and properties, Materials in Harsh Environments, Mesoscale modeling and simulation, Nuclear materials, Numerical methods

Lab Website: Tonks Research Group

Photo of Justin Watson Justin WatsonAssociate Professor and NE Graduate Coordinator
Work Rhines 178 (352) 273-0241

Ph.D., 2010, Penn State University

Research Interests: Reactor Kinetics and Dynamics, Neutronics, Thermal Hydraulics, Multiphysics Simulation, Advanced Numerical Methods, Applied Mathematics, Advanced Code Coupling Techniques, Scientific Software Development, High Performance Computing

Lab Website: Florida Advanced Multiphysics Modeling and Simulation (FAMMoS) Lab