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Necdet Serhat Aybat is a Professor at the Harold Inge Marcus Department of Industrial and Manufacturing Engineering at Penn State University. His research primarily focuses on Operations Research, particularly in areas like Large-Scale Convex Optimization, Compressive Sensing, Matrix Rank Minimization, Robust Stable PCA, and Distributed Algorithms. Professor Aybat has authored numerous publications, including the noteworthy book 'Handbook Robust Low Rank Sparse Matrix Decomposition: Applications Image Video Processing'. His academic contributions are highlighted by his collaboration on several journal articles and conference papers that explore advanced methodologies in optimization and control systems. Over the years, he has received multiple awards, including the IEEE INFOCOM 2017 “Best-in-Session-Presentation” award and has been recognized as a finalist for the INFORMS Data Mining Student Paper Prize as an advisor. His commitment extends beyond research, as he actively participates in organizing significant conferences and serves in various leadership roles within professional societies. With a focus on both rigorous theoretical foundations and practical applications, Professor Aybat continues to influence the field of industrial engineering through his role in academia and research.
The Pennsylvania State University • Park, PA
Teaching and conducting research in industrial and manufacturing engineering.
GRE scores are highly recommended but not strictly required for Applied Linguistics.