Garritt Tucker

Thierry Ouisse


Colorado School of Mines, USA

Professor Tucker is an Associate Professor in the Mechanical Engineering Department at the Colorado School of Mines in Golden, CO. He joined the faculty at Mines in the summer of 2017 as an Assistant Professor and has been active in the interdisciplinary Materials Science program and the Alliance for the Development of Additive Processing Technologies with active collaborations with both the National Renewable Energy Laboratory (Golden, CO) and Los Alamos National Laboratory (Los Alamos, NM). Before moving to Mines, he spent 4 years as an Assistant Professor in the Department of Materials Science and Engineering at Drexel University (Philadelphia, PA), and 2 years as a Postdoctoral Research Appointee at Sandia National Laboratories (Albuquerque, NM) in the Computational Materials and Data Science group. While at Drexel, he was awarded the Outstanding Teacher Award in 2015 and the TMS Young Leader Professional Development Award in 2016 for the Materials Processing and Manufacturing Division.

Professor Tucker earned his Ph.D. in 2011 from the Georgia Institute of Technology (Atlanta, GA) in the School of Materials Science and Engineering, and a B.S. in 2004 from Westminster College (Salt Lake City, UT) majoring in both Physics and Mathematics. During his undergraduate career, he was an Academic All-American and co-captain in varsity soccer and was awarded the Outstanding Physics Senior Award. At Georgia Tech, he participated in the Enabling Predictive Science Research Institute at Sandia National Laboratories (Livermore, CA) as a student intern, and was nominated for the Sigma Xi award for best thesis. At Mines, his research ambitions are aimed at integrating high-performance computing, materials theory, and novel computational tools to discover the fundamental structure-property relationships of emerging materials that will enable the predictive design of advanced materials with tunable properties. At the core of Prof. Tucker’s research group approach is to develop collaborations and programs that effectively mesh computation with experiment to tailor functional materials.