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Daniel Kuhn is a professor of Operations Research at the College of Management of Technology at École Polytechnique Fédérale de Lausanne (EPFL), where he holds the Chair in Risk Analytics and Optimization. His current research focuses on data-driven optimization and the development of efficient computational methods for solving stochastic robust optimization problems. With interests spanning engineered systems, machine learning, business analytics, and finance, Kuhn emphasizes application-driven work. Before joining EPFL, he was a faculty member in the Department of Computing at Imperial College London from 2007 to 2013 and held a postdoctoral research associate position in the Department of Management Science and Engineering at Stanford University from 2005 to 2006. Kuhn holds a PhD in Economics from the University of St. Gallen and an MSc in Theoretical Physics from ETH Zurich. He is the editor-in-chief of Mathematical Programming and has published extensively in the fields of operations research, optimization, and machine learning.
École Polytechnique Fédérale de Lausanne • Lausanne, Switzerland
Professor of Operations Research, Chair in Risk Analytics and Optimization.
Imperial College London • London, United Kingdom
Faculty member in the Department of Computing.
Stanford University • Stanford, California, USA
Postdoctoral research associate in the Department of Management Science and Engineering.
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