Johann Guilleminot
Civil and Environmental Engineering
Paul Ruffin Scarborough Associate Professor of Engineering
Research Interests
Computational mechanics, mechanics of heterogeneous materials, molecular dynamics simulations and atomistic-to-continuum coupling, stochastic solvers, statistical inverse problem and model validation, stochastic analysis, uncertainty quantification in science and engineering
Bio
Johann Guilleminot is the Paul Ruffin Scarborough Associate Professor of Engineering and an Associate Professor of Civil and Environmental Engineering at Duke University. He joined Duke on July 1, 2017.
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Prior to that, he held a Maître de Conférences position in the Multiscale Modeling and Simulation Laboratory at Université Paris-Est in France.
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He earned an MS (2005) and PhD (2008) in Theoretical Mechanics from the University of Lille 1 Science and Technology (France), and received his Habilitation (2014) in Mechanics from Université Paris-Est. Habilitation is the highest academic degree in France.
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Dr. Guilleminot’s research focuses on uncertainty quantification, computational mechanics and materials science, as well as on topics at the interface between these fields. He is particularly interested in the multiscale analysis of linear/nonlinear heterogeneous materials (including biological and engineered ones), homogenization theory, scientific machine learning, statistical inverse problems and stochastic modeling with applications for computational science and engineering.
Education
- M.S. Lille University of Science and Technology (France), 2005
- Ph.D. Lille University of Science and Technology (France), 2008
Positions
- Paul Ruffin Scarborough Associate Professor of Engineering
- Associate Professor in the Department of Civil and Environmental Engineering
- Associate Professor in the Thomas Lord Department of Mechanical Engineering and Materials Science
Courses Taught
- MENG 551: Master of Engineering Internship/Project Assessment
- MENG 550: Master of Engineering Internship/Project
- ME 758S: Curricular Practical Training
- ME 582: Applications in Data and Materials Science
- ME 524: Introduction to the Finite Element Method
- EGR 393: Research Projects in Engineering
- COMPSCI 583: Applications in Data and Materials Science
- CEE 780: Internship
- CEE 628: Uncertainty Quantification in Computational Science and Engineering
- CEE 530: Introduction to the Finite Element Method
- CEE 421L: Matrix Structural Analysis
- CEE 394: Research Independent Study in Civil and Environmental Engineering