Dejan Slepčev

Dejan Slepčev is a Professor in the Department of Mathematical Sciences at Carnegie Mellon University, serving as Mellon College of Science Associate Dean for Faculty and Graduate Affairs. His research primarily focuses on applied analysis, utilizing partial differential equations, calculus of variations, optimal transportation, probability, statistics, functional analysis, and scientific computation to address applied problems. His work includes developing mathematical frameworks for variational and PDE-based problems on random data samples and studying collective behavior of systems of interacting particles. He is also interested in energy-driven systems and their dynamics, including pattern-forming systems and the evolution of interfaces. His research has applications in data science, machine learning, and computational methods.

Dejan Slepčev is a Professor of Mathematical Sciences at Carnegie Mellon University, specializing in applied analysis, machine learning, and partial differential equations. His research focuses on the mathematical foundations of signal processing, machine learning, and nonlocal interaction equations. He has contributed to the development of optimal mass transport frameworks for analyzing variations in image sets and has explored the consistency of spectral clustering and semi-supervised learning algorithms. His work also includes the analysis of nonlinear mobility continuity equations and the existence of ground states of nonlocal-interaction energies. Slepčev's research bridges applied mathematics and data science, with applications in signal analysis, image processing, and machine learning.