Introduction

Welcome to the Uncertainty Quantification Group, in the Department of Aeronautics and Astronautics at MIT. We are part of the Aerospace Computational Design Laboratory and affiliated with the Center for Computational Engineering.

Research Overview

Our research focuses on advancing fundamental computational methodology for uncertainty quantification and statistical inference in complex physical systems, and using these tools to address challenges in modeling energy conversion and environmental applications.

We tackle a broad range of projects, but most involve aspects of a few core questions:

  • How to quantify confidence in computational predictions?
  • How to build or refine models of complex physical processes from indirect and limited observations?
  • What information is needed to drive inference, design, and control?

Featured Publications

A. Spantini, R. Baptista, Y. M. Marzouk
Preprint (2019)
O. Zahm, T. Cui, K. Law, A. Spantini, Y. M. Marzouk
Preprint (2018)
M. Parno, Y. M. Marzouk
SIAM/ASA Journal on Uncertainty Quantification 6 pp. 645–682 (2018)
A. Spantini, D. Bigoni, Y. M. Marzouk
The Journal of Machine Learning Research 19 pp. 1–71 (2018)

View all publications

Announcements

November 2019
Congratulations to Jakob Zech for accepting a faculty position in the Institute of Applied Mathematics at the University of Heidelberg!

September 2019
Congratulations to Ben Zhang for winning the MathWorks Fellowship from the MIT School of Engineering.

May 2019
Congratulations to Zheng Wang for successfully defending his PhD thesis!

February 2019
Congratulations to Fengyi Li for passing her doctoral qualifying exams.

May 2018
Congratulations to Andrew Davis for successfully defending his PhD thesis!

February 2018
Congratulations to Xun Huan for accepting a tenure-track position at the University of Michigan!

September 2017
Congratulations to Olivier Zahm for accepting a permanent position at INRIA in Grenoble!

August 2017
Congratulations to Alessio Spantini for successfully defending his PhD thesis, "On the low-dimensional structure of Bayesian inference!"

More announcements