Dr. Prajay Patel is an Assistant Professor in Chemistry at the University of Dallas. His teaching disciplines cover the area of Physical Chemistry, Basic Ideas in Forensic Chemistry, Computational Chemistry, and Inorganic Chemistry. Dr. Prajay Patel completed his B.S. in Chemistry and Mathematics at University of Texas at Arlington in 2014, and a Ph.D. in Physical Chemistry at Michigan State University in 2019. Prior to moving to his current institution in 2022, he was previously a postdoctoral appointee in the Catalysis Science Group of the Chemical Sciences and Engineering Division at Argonne National Laboratory. Dr. Prajay Patel has received awards and honors such as the Molecular Sciences Software Institute (MolSSI) Accelerating Curricular Transformation in the Computational Molecular Sciences (ACT-CMS) 2025 Faculty Fellow and the Impact Argonne Award (2021), among others, and is a member of the American Chemical Society. His research interests focus on computational catalysis, development of computational methods and machine learning models for thermochemistry, computational X-ray absorption spectroscopy, and catalysis.
Dr. Prajay Patel is an Assistant Professor in Chemistry at the University of Dallas. His teaching disciplines cover the area of Physical Chemistry, Basic Ideas in Forensic Chemistry, Computational Chemistry, and Inorganic Chemistry. Dr. Prajay Patel completed his B.S. in Chemistry and Mathematics at University of Texas at Arlington in 2014, and a Ph.D. in Physical Chemistry at Michigan State University in 2019. Prior to moving to his current institution in 2022, he was previously a postdoctoral appointee in the Catalysis Science Group of the Chemical Sciences and Engineering Division at Argonne National Laboratory. Dr. Prajay Patel has received awards and honors such as the Molecular Sciences Software Institute (MolSSI) Accelerating Curricular Transformation in the Computational Molecular Sciences (ACT-CMS) 2025 Faculty Fellow and the Impact Argonne Award (2021), among others, and is a member of the American Chemical Society. His research interests focus on computational catalysis, development of computational methods and machine learning models for thermochemistry, computational X-ray absorption spectroscopy, and catalysis.