Principal Investigator

Youssef Marzouk
Youssef Marzouk

Youssef Marzouk  

Youssef Marzouk is a Professor in the Department of Aeronautics and Astronautics at MIT, and co-director of the MIT Center for Computational Science & Engineering. He is also a core member of MIT's Statistics and Data Science Center and director of the MIT Aerospace Computational Design Laboratory. His research interests lie at the intersection of computation and statistical inference with physical modeling. He develops new methodologies for uncertainty quantification, Bayesian modeling and computation, data assimilation, experimental design, and machine learning in complex physical systems. His methodological work is motivated by a wide variety of engineering, environmental, and geophysics applications. He received his SB, SM, and PhD degrees from MIT and spent four years at Sandia National Laboratories before joining the MIT faculty in 2009. He is a recipient of the Hertz Foundation Doctoral Thesis Prize, the Sandia Laboratories Truman Fellowship, the US Department of Energy Early Career Research Award, and the Junior Bose Award for Teaching Excellence from the MIT School of Engineering. He is an Associate Fellow of the AIAA and currently serves on the editorial boards of the SIAM Journal on Scientific Computing, the SIAM/ASA Journal on Uncertainty Quantification, and several other journals. He is also an avid coffee drinker and occasional classical pianist.

Research Scientists

Jayanth Jagalur
Jayanth Jagalur

Jayanth Jagalur  

My research is broadly in the field of UQ and inverse problems. Other areas that interest me are, multi-scale methods, adaptivity, iterative solvers, and HPC. Prior to joining the group I was at RPI, where I obtained an M.S. in Applied Mathematics and PhD. in Mechanical Engineering. My dissertation research involved developing variational multi-scale methods for deterministic and stochastic wave equations. Outside my work, I usually prefer to spend time in the outdoors, indulge in culinary exploits or continue my quest to learn music.

Postdoctoral Associates

Paul-Baptiste Rubio
Paul-Baptiste Rubio

Paul-Baptiste Rubio  

Paul-Baptiste's bio.

Graduate Students, PhD

Michael Brennan
Michael Brennan

Michael Brennan  

My research is broadly in the area of numerical methods for uncertainty quantification and mathematical modeling. I am currently interested in techniques that exploit multi-scale/multi-feature structure in a system's dynamics. These methods accelerate large scale computations. Before joining MIT, I received an M.S. in Mathematics from Virginia Tech, where I studied nonlinear eigenvalue problems and reduced order modeling. Outside of work, I enjoy cooking, snowboarding, and exploring Boston.
Hannah Diehl
Hannah Diehl

Hannah Diehl  

Hannah's bio!
Chi Feng
Chi Feng

Chi Feng  

My research interests include optimal experimental design in the presence of model error and other topics in uncertainty quantification. I received my bachelor's degree in Physics from the California Institute of Technology. Outside of my work, I am interested in classical piano, photography, web design, and the culinary arts.
Fengyi Li
Fengyi Li

Fengyi Li  

My current research is related to machine learning, inference, and optimal experimental design. In addition, I am interested in Bayesian statistics, optimization and applied probability. I was born and raised in Zhengzhou, China and lived in College Station, Texas for a few years, where I received my Bachelor’s degrees in Mathematics and Mechanical Engineering from Texas A&M University. In my free time, I enjoy playing tennis and listening to music.
Ricardo Miguel Baptista
Ricardo Miguel Baptista

Ricardo Miguel Baptista   www

My current research focuses on the optimization of coupled multi-physics systems. I am also interested in high-dimensional problems, compressive sensing, and machine learning techniques. I grew up in Toronto and graduated in 2015 from the Engineering Science program at the University of Toronto. Before joining MIT, I also worked in Flight Sciences at Bombardier Aerospace. In my free time, I enjoy swimming and traveling.
Robert Ren
Robert Ren

Robert Ren  

Robert's bio!
Andrea Scarinci
Andrea Scarinci

Andrea Scarinci  

I am interested in uncertainty quantification applications in aircraft systems design and multidisciplinary optimization. I am also interested in machine learning techniques and natural language modeling to facilitate systems engineering processes. I have previously worked as a propulsion control engineer at Airbus for two years before moving to Boston. Outside work, I am part of the MIT chamber choir and passionate about music, cinema and anthropology.
Benjamin Zhang
Benjamin Zhang

Benjamin Zhang  

My current research is related to Bayesian inference and filtering. I am also generally interested in numerical methods for stochastic modeling and PDEs. I was born in China, but I spent most of my years growing up in Canada and the San Francisco Bay Area. I graduated in 2015 from UC Berkeley, where I received my Bachelor's degrees in Engineering Physics and Applied Mathematics. Outside of work, come talk to me about politics, history, cartography, intrigue, conspiracy, and gripping denouement.

Graduate Students, SM

Adrianna Boghozian
Adrianna Boghozian

Adrianna Boghozian  

Adrianna's bio!
Kelvin Leung
Kelvin Leung

Kelvin Leung  

Kelvin's bio!
Aimee Maurais
Aimee Maurais

Aimee Maurais  

Aimee's bio!

Undergraduate Students (UROP)

Luann Jung
Luann Jung

Luann Jung  

Luann's bio!
Joshua White
Joshua White

Joshua White  

Josh bio!

Alumni

Research Scientists

Postdoctoral Associates

  • Florian Augustin (MathWorks)
  • Ingrid Berkelmans (Australia Future Fund)
  • Tiangang Cui (Senior Lecturer, Monash University)
  • Sonjoy Das (Assistant Professor, University at Buffalo)
  • Michalis Frangos (Schlumberger)
  • Nikhil Galagali (Apple, Inc.)
  • Xun Huan (Assistant Professor, University of Michigan)
  • Jinglai Li (Professor, University of Birmingham)
  • Alexandre Marques (MIT)
  • Rebecca Morrison (Assistant Professor, University of Colorado Boulder)
  • Matthew Parno (Dartmouth College and Cold Regions Research and Engineering Laboratory)
  • Antti Solonen (Lappeenranta University of Technology and Eniram)
  • Alessio Spantini (Bridgewater Associates)
  • Ankur Srivastava (Uptake Technologies)
  • Luca Tosatto (Bridgewater Associates)
  • Olivier Zahm (INRIA Grenoble)
  • Jakob Zech (Juniorprofessor, University of Heidelberg)

Long Term Visitors

  • Daniele Bigoni (Technical University of Denmark)
  • Ben Calderhead (Imperial College London)
  • Weiqi Ji (Tsinghua University)
  • Dominic Kohler (Siemens AG)
  • Jinglai Li (Shanghai Jiaotong University)
  • Lionel Mathelin (LIMSI/CNRS France)
  • Friedrich Menhorn (TU Munich)
  • Sebastian Springer (Lappeenranta University of Technology)
  • Faidra Stavropoulou (TU Munich)
  • Jouni Susiluoto (Jet Propulsion Laboratory & Finnish Meteorological Institute)
  • Lara Welder (RWTH Aachen)

PhD Students

  • Raghav Aggarwal (graduated January 2018)
    • Thesis: A phase field model for the gallium permeation of aluminum grain boundaries (co-advised with Michael Demkowicz)
    • Affiliation: VulcanForms
  • Patrick Conrad (graduated April 2014)
    • Thesis: Accelerating Bayesian inference in computationally expensive computer models using local and global approximations 
    • Affiliation: Cherish Health
  • Andrew Davis (graduated May 2018)
    • Thesis: Prediction under uncertainty: from models for marine-terminating glaciers to Bayesian computation (co-advised with Patrick Heimbach)
    • Affiliation: Courant Institute, New York University
  • Nikhil Galagali (graduated December 2015)
    • Thesis: Bayesian inference of chemical reaction networks
    • Affiliation: Apple, Inc.
  • Alex Gorodetsky (graduated September 2016)
    • Thesis: Continuous low-rank tensor decompositions, with applications to stochastic optimal control and data assimilation (co-advised with S. Karaman)
    • Affiliation: Assistant Professor, University of Michigan
  • Xun Huan (graduated August 2015)
    • Thesis: Numerical approaches for sequential Bayesian optimal experimental design
    • Affiliation: Assistant Professor, University of Michigan
  • Antoni Musolas (graduated March 2020)
    • Thesis: Covariance estimation on matrix manifolds
    • Affiliation: Farallon Capital Management
  • Matthew Parno (graduated October 2014)
    • Thesis: Transport maps for accelerated Bayesian computation 
    • Affiliation: Cold Regions Research and Engineering Laboratory and Dartmouth College
  • Jon Paul (JP) Janet (graduated December 2019)
    • Thesis: Multifidelity methods for design of transition metal complexes (co-advised with Heather Kulik)
    • Affiliation: AstraZeneca
  • Alessio Spantini (graduated August 2017)
    • Thesis: On the low-dimensional structure of Bayesian inference
    • Affiliation: Bridgewater Associates
  • Zheng Wang (graduated June 2019)
    • Thesis: Optimization-based sampling in function space for Bayesian inverse problems
    • Affiliation: Kaleidoglobe

SM Students

  • Thomas Coles (MIT)
  • Lucio Di Ciaccio (The Carlyle Group)
  • Naveen Krishnakumar (Grantham Mayo van Otterloo)
  • Subhadeep Mitra (Two Sigma Investments)

Undergraduate Students

  • Erick Fuentes (Fitbit)
  • George Hansel (Google)
  • Savithru Jayasinghe (Cambridge University)
  • Hadi Kasab (American University of Beirut)
  • Tomas Kogan (Cambridge University)
  • Michael Lieu (Aurora Flight Sciences)
  • Kevin Lim (University of Toronto, Department of Economics)
  • Ali Saab (American University of Beirut)
  • Yair Shenfeld (Princeton University, ORFE)