Regular biography
Mykhaylo Shkolnikov is a Professor in the Department of Mathematical Sciences at Carnegie Mellon University. His research focuses on interacting particle systems in mathematical finance, mathematical physics, and neuroscience, utilizing stochastic analysis and PDE/SPDE techniques. His work spans probability theory, random operators, integrable probability, and probabilistic approaches to PDEs. He has published extensively in top-tier journals, including contributions to the supercooled Stefan problem, McKean-Vlasov equations, and free boundary problems. His research also includes convergence of time-stepping schemes and scaling limits of multi-particle DLA models.
Scholar-generated biography
Mykhaylo Shkolnikov is a researcher at Carnegie Mellon University, specializing in Probability Theory, Mathematical Finance, Mathematical Physics, and Partial Differential Equations. His work explores complex systems of interacting particles and their applications in financial modeling and stochastic processes. He has published extensively on topics such as systemic risk modeling, rank-based stochastic equations, and mean field systems. His research bridges theoretical mathematics with practical applications in finance and physics, focusing on stochastic equations, diffusion processes, and large deviation principles. His contributions include studies on supercooled Stefan problems, forward performance processes, and intertwining diffusions.