Markov chains and processes, random walks, stationary, independent increments, and Poisson processes. Ergodicity. Examples (e.g., diffusion, queuing theory, etc.).

A second course in stochastic processes and applications to insurance. Markov chains (discrete and continuous time), processes with jumps; Brownian motion and diffusions; Martingales; stochastic ...

Natural processes, such as rain falling, the motion of groups of insects or birds, or the random movement of smoke particles in air may be described as stochastic.

A stochastic correlation approach using copula functions offers a flexible alternative. By allowing correlations to vary ...

Throughout, we will be applying some of the theoretic results to the analysis of queues. Students are expected to have some background in probability (such as IEMS 202) and stochastic processes; no ...

The 2025 edition of the traditional Boltzmann Lecture will be held on Thursday, February 20th, at 14:00 in Room 128-129. Professor Satya Majumdar from CNRS and Universite Paris-Sud, Orsay will give a ...

Statistics, and real analysis at the undergraduate engineering or mathematics level; graduate level probability and stochastic processes (IEMS 460-1); computer programming in Python; graduate standing ...