Petros Koumoutsakos
APMTH 207 | Fall 2025 | Course Listing | Canvas Site
Monday & Wednesday, 1:30 PM – 2:45 PM
The class aims to highlight the process of scientific discovery under uncertainty in the age of data. The class content stresses a unifying approach to data driven modeling and inference through stochastic simulations, optimization and Bayesian uncertainty quantification. The class projects require transferring an idea to software in multi- and many-core computer architectures.
Recommended Prep: STAT 110, CS 50 or proficiency in a computer programming language (C++ and python strongly recommended) as well as CS 107.