Houman Owhadi
Professor of Applied and Computational Mathematics and Control and Dynamical Systems
B.S., Ecole Polytechnique (France), 1994; M.S., Ecole Nationale des Ponts et Chaussees, 1997; Ph.D., Ecole Polytechnique Federale de Lausanne (Switzerland), 2001. Assistant Professor, Caltech, 2004-11; Professor, 2011-.
Research interests: statistical numerical approximation, numerical homogenization, operator adapted wavelets, fast solvers, Gaussian process regression, machine learning, multi-scale and stochastic analysis, stochastic mechanics and geometric integration, uncertainty quantification
Overview
Professor Owhadi's research concerns the exploration of interplays between numerical approximation, statistical inference and learning from a game theoretic perspective. Whereas the process of discovery is usually based on a combination of trial and error, insight and plain guesswork, his research is motivated by the facilitation/automation possibilities emerging from these interplays.
Related Courses
2023-24
ACM 118 – Stochastic Processes and Regression
ACM/IDS 216 – Markov Chains, Discrete Stochastic Processes and Applications
2022-23
ACM 118 – Stochastic Processes and Regression
ACM/IDS 216 – Markov Chains, Discrete Stochastic Processes and Applications
2021-22
ACM 118 – Stochastic Processes and Regression
ACM/IDS 216 – Markov Chains, Discrete Stochastic Processes and Applications
2020-21
ACM 118 – Stochastic Processes and Regression
ACM/IDS 216 – Markov Chains, Discrete Stochastic Processes and Applications