Mustafa A. Mohamad
I'm a postdoctoral research fellow at the Courant Institute of Mathematical Sciences. Formerly, I was a
research assistant at the Massachusetts Institute of Technology, where I completed my S.M. and Ph.D. degrees in
Mechanical Engineering and Computation. Before then, I was an undergraduate student at the University of
Illinois at Urbana-Champaign where I received my B.Sc. in Engineering Mechanics and a minor in Mathematics.
Feel free to reach out to me via email: mus-m at outlook.com
Research & Work
My research expertise lies at the intersection of computational mathematics, stochastic modelling, dynamical
systems, machine learning, and data assimilation. More generally, my work focuses on uncertainty
I have worked on efficient methods to quantify extreme events (bursting phenomena) in physical
systems. This research involved developing new strategies by blending ideas from probability and dynamical
The most recent angle of this work involved utilizing Gaussian process regression and techniques from machine
learning to develop efficient sampling algorithms that target heavy-tailed statistics.
Recently, my work is centered around data assimilation and Bayesian parameter estimation methods using noisy
continuous measurements for the prediction of particles in dynamic environments and
the statistical properties of the fields generating such motions, for high
I also enjoy contributing to open source software; in particular the Julia language and packages in the Julia
ecosystem. My projects and
contributions are available on Github.
Most of my journal publications should be available on Google Scholar and arXiv. You may also contact
me via email for preprints.
- M. A. Mohamad, A. J. Majda, Eulerian and Lagrangian statistics in an exactly solvable turbulent shear model with a random background mean, submitted
- M. A. Mohamad, A. J. Majda, Recovering the Eulerian energy spectrum from noisy Lagrangian tracers, submitted
- M. A. Mohamad, T. P. Sapsis, A sequential sampling
strategy for extreme event statistics in nonlinear dynamical systems, Proceedings of the
National Academy of Sciences, 115, p. 11138-11143, Oct 2018. [pdf] [supporting information]
- H. K. Joo, M. A. Mohamad, T. P. Sapsis, Heavy-tailed
response of structural systems subjected to extreme
forcing events, ASME Journal of Computational and Nonlinear Dynamics, Volume 13 (9),
Jul 2018. [pdf]
- H. K. Joo, M. A. Mohamad, T. P. Sapsis, Extreme events and their
optimal mitigation in nonlinear structural systems excited by stochastic loads: Application to ocean
engineering systems, Ocean Engineering, Volume 142, pp. 145-160, Sept 2017. [pdf]
- M. A. Mohamad, W. Cousins, T. P. Sapsis, A probabilistic
decomposition-synthesis method for the
quantification of rare events due to internal instabilities, Journal of Computational
pp. 288-308, Oct 2016. [pdf]
- M. A. Mohamad, T. P. Sapsis, Probabilistic response and
rare events in Mathieu's equation under correlated
parametric excitation, Journal of Ocean Engineering, Volume 120, pp. 289-297, Jul. 2016. [pdf]
- M. A. Mohamad, T. P. Sapsis, Probabilistic
description of extreme events in intermittently unstable systems
excited by correlated stochastic processes, SIAM/ASA Journal on Uncertainty Quantification,
pp. 709-736, Aug 2015. [pdf]
- M. A. Mohamad, T. P. Sapsis, Efficient sampling for extreme event statistics of the wave loads on an
offshore platform, The 30th American Towing Tank Conference, West Bethesda, Maryland, Oct 2017.
- T. P. Sapsis, M. A. Mohamad, Probabilistic quantification of extreme events in complex systems, 9th
European Nonlinear Dynamics Conference, Budapest, Hungary, Jun 2017.
- T. P. Sapsis, M. A. Mohamad, H. K. Joo, Extreme response mitigation of stochastically forced nonlinear
structures, 9th European Nonlinear Dynamics Conference, Budapest, Hungary, Jun 2017.
- M. A. Mohamad, T. P. Sapsis, Probabilistic response of Mathieu equation excited by correlated parametric
excitation, Proceedings of STAB 2015, Glasgow, UK, Jun 2015.
- M. A. Mohamad, T. P. Sapsis, Analytical approximation of the heavy-tail structure for intermittently
unstable complex modes, Proceedings of the Dynamic Data Driven Environmental Systems Science
Cambridge, Massachusetts, Nov 2014.