Dr. Pejman Tahmasebi is an Associate Professor at the Colorado School of Mines. For his Ph.D., he worked on the modeling of large- and small-scale porous media using data analytics methods in a joint program under the supervision of Prof. Sahimi from the University of Southern California. He then joined Stanford University as a postdoc and worked on statistical modeling for data integration and uncertainty modeling. Then, he worked as an associate research scientist at the University of Texas at Austin on the development of novel statistical and multiscale techniques. He then conducted research at Caltech on granular particles for geomechanical applications, in the Department of Mechanical and Civil Engineering. Dr. Tahmasebi has published several papers and five book chapters.
Dr. Tahmasebi has also received several awards and recognitions, including two international awards given to rising stars by the International Association for Mathematical Geosciences (IAMG) and the European Association of Geoscientists and Engineers (EAGE), two regional awards from SPE on Reservoir Description and Dynamics and Data Analytics, and also the Best Paper Award from Elsevier.
Dr. Tahmasebi is on the editorial board of three leading journals (Water Resources Research, Computers & Geosciences, and Fluids) handling papers on machine learning, subsurface systems, and multiscale and multiphysics modeling.
- Geomechanics: From granular particles to large-scale systems, THMC processes
- Subsurface Systems (Energy, Water, Storage): Computational Modeling and Multiple point statistics
- Machine Learning: Physics-guided AI
- Fluid Flow in Porous Media