Dejan Slepčev

Dejan Slepčev is a Professor and Associate Dean for Faculty and Graduate Affairs at the Mellon College of Science, Department of Mathematical Sciences, Carnegie Mellon University. His research focuses on applied analysis, with applications to data science, collective behavior of particle systems, and energy-driven systems. He holds a Ph.D. from the University of Texas at Austin.

His research interests include partial differential equations, calculus of variations, optimal transportation, and their applications to machine learning tasks such as clustering and classification. He develops mathematical frameworks for analyzing variational and PDE-based problems on random data samples, improving algorithms for data science. He also studies systems of interacting particles, particularly those modeling collective behavior in biological and physical systems, and energy-driven systems involving pattern formation and interface evolution.

His work bridges theoretical analysis and computational methods, addressing challenges in data analysis, image processing, and the dynamics of complex systems. Key contributions include studies on spectral clustering, graph-based semi-supervised learning, and the continuum limits of discrete variational problems.

• Education: Ph.D., University of Texas at Austin.