Pierre Patie

Pierre Patie is a Professor at Cornell University's School of Operations Research and Information Engineering (ORIE). His research focuses on stochastic processes, spectral theory, and their applications in financial mathematics, neurology, and mathematical physics. He explores topics such as isospectral classes of linear operators, first passage time problems, and hypocoercivity via spectral methods.

His research interests include:

• Isospectral classes of linear operators (unitary conjugation, interweaving, weak similarity)
• Spectral theory of non-selfadjoint operators
• First passage time problems for Markov processes
• Subdiffusive processes and boundary crossing phenomena
• Financial mathematics and risk-neutral pricing
• Special functions and moment problems

Pierre has advised numerous PhD students at Cornell and other institutions, including work on topics like non-reversible Markov chains, spectral expansions, and self-similar processes. He co-authored over 50 publications and collaborates with researchers globally. His work bridges probability theory, analysis, and applications in finance and neuroscience.

Pierre co-organizes the Cornell Probability Seminar and the Finger Lakes Probability Seminar. He has contributed to conferences such as the Intertwining between Probability, Analysis and Statistical Physics workshop in Singapore (2024).