Qais received a dual Ph.D. degrees in operation research and industrial engineering from Pennsylvania State University/University Park in August 2015. In his role as computer scientist/statistician at FDA, he conducts research in statistical/operational modeling and computer science at Center of Drug Evaluation and Research (CDER)/ Office of Translational Science (OTS)/ Office of Computational Science (OCS) in the U.S. Food and Drug Administration (FDA). Specifically, he applies advanced statistical modeling and scientific computing techniques to computationally intensive tasks that are encountered in regulatory and scientific applications. For this purpose, he utilizes various statistical and operations research methodologies such as machine learning and data mining algorithms, natural language processing (NLP) techniques, Neural Networks procedures, and text analytics to extract meaning, patterns and hidden structures in structured and unstructured data; identifying the most feasible approaches to software/networking system design and development problems; consulting reviewers, fellow scientists, and regulations to analyze problems and recommend technology based solutions. He also prepares reports and manuscripts based on research findings and will present at scientific meetings as necessary. Moreover, he is an active member in several working groups across FDA such as the Modeling and Simulation Workgroup, INFORMED and HIVE.
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