Amir Shahmoradi is an assistant professor in the College of Science's Department of Physics and Division of Data Science at the University of Texas at Arlington. He earned his Ph.D. in theoretical and computational physics from the University of Texas at Austin in 2015. From 2015 to 2018, he held a Peter O’Donnell Postdoctoral Fellowship in Computational Engineering and Science at UT Austin and an Adjunct Professor position in the Department of Aerospace Engineering and Engineering Mechanics at UT Austin. Shahmoradi has extensive research experience and education in Data Science, Machine Learning, and Artificial Intelligence tools, techniques, and algorithms. His research interests include mathematical modeling, uncertainty quantification, the development of statistical algorithms for optimization, sampling, and integration of high-dimensional mathematical objective functions, and applying these methods to data-intensive fields of science.