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Hamed Hassani is an Associate Professor in the Department of Electrical and Systems Engineering, as well as in the Departments of Computer and Information Sciences and Statistics at the University of Pennsylvania. He earned his PhD in Computer and Communication Sciences from EPFL, Lausanne. Prior to his current role, he was a research fellow at the Simons Institute for the Theory of Computing at UC Berkeley and a post-doctoral researcher at ETH Zurich. His research interests encompass machine learning, coding theory, and information theory, with a focus on developing robust algorithms for data science applications.On Coursera, Hamed teaches the course Statistics for Data Science Essentials, which is designed to provide learners with foundational statistical concepts essential for data science. His expertise and innovative teaching methods aim to equip students with the necessary skills to analyze data effectively and make informed decisions based on statistical analysis. Hamed's contributions to the field have been recognized through various awards, including the IEEE Information Theory Society's Thomas M. Cover Dissertation Award and the NSF CAREER Award.