Dr. Dejan Slepčev

Biography

Dejan Slepčev is a Professor in the Department of Mathematical Sciences at Carnegie Mellon University. His primary research focus is in applied analysis, employing techniques such as partial differential equations, calculus of variations, optimal transportation, probability, statistics, and functional analysis to tackle practical problems across a broad range of applications. Through his work, he investigates complex data science challenges facilitated by modern data acquisition methods, which yield vast amounts of information. His research notably addresses key topics in machine learning and statistical tasks like clustering, classification, dimensionality reduction, and regression, framing them as optimization problems. Slepčev is also engaged in the mathematical study of collective behaviors in systems of interacting particles or agents, particularly where long-range interactions occur in biological or physical models. His work on energy-driven systems seeks to understand the dynamics of patterns formed due to energy dissipation, which illuminates the underlying geometric structures of the configuration space. His contributions to the field are underscored by multiple significant publications, which explore various aspects of these complex systems and their mathematical foundations.

Research Interests