Computational Science and Engineering

Image of computer generated molecule

Instructional molecular simulation module describing osmosis

Research in Computational and Data-Enabled Science and Engineering focuses on thermodynamic behavior, fluid dynamics, reaction mechanisms (both biological and chemical), bioinformatics, and modeling devices and systems.

Our researchers employ a full spectrum of techniques from quantum mechanics through molecular simulation to continuum mechanics. Our approach focuses on bringing data-driven discovery and rational design to all areas of our chemical and biological research. 

Current Research Projects

Computational and Data-Enabled Science and Engineering Faculty

Michel Dupuis - Chemistry fundamentals for new energy technologies from multi-physics multi-scale modeling

Jeff Errington - Molecular simulation, statistical thermodynamics, interfacial phenomena.

Ed Furlani - Computational physics/multidisciplinary modeling: microfluidics, computational fluid dynamics, heat/mass transfer, multiphase and inkjet systems, optofluidics, MEMS design and simulation, biomagnetics, nanophotonics.

Johannes Hachmann - Computational chemistry and materials science, virtual high-throughput and Big Data, machine learning, electronic structure theory and methods, quantum effects in catalysis and materials, rational design.

David A. Kofke - Statistical physics, molecular modeling and simulation, software engineering.