Mykhaylo Shkolnikov

Mykhaylo Shkolnikov is a Professor at Carnegie Mellon University's Department of Mathematical Sciences within the Mellon College of Science. His research focuses on interacting particle systems with applications in mathematical finance, mathematical physics, and neuroscience, employing stochastic analysis and PDE/SPDE tools.

Education:

• Ph.D., Stanford University
• Postdoctoral Appointments: Department of Statistics, UC Berkeley; Mathematical Sciences Research Institute (MSRI), Berkeley

His work spans probability theory (random operators, integrable probability, large deviations) and PDEs (supercooled Stefan problem, free boundary analysis). Recent publications address global solutions, uniqueness, and numerical methods for Stefan problems, alongside mean field models and financial applications.

Scientific Awards:

• SIAM Early Career Prize
• INFORMS Erlang Prize
• Princeton Faculty Advancement Award
• Princeton Teaching Commendation

He is affiliated with the Center for Nonlinear Analysis at Carnegie Mellon, contributing to interdisciplinary research on stochastic systems and nonlinear PDEs.