World's Best Scientists 2026 revealed!
Youssef M. Marzouk

Youssef M. Marzouk

D-Index & Metrics

Computer Science

D-Index
41
Citations
7515
World Ranking
8815
National Ranking
3766

Overview

Youssef M. Marzouk is affiliated with MIT in the United States. Their research contributions span the fields of computer science and mathematics, with a significant focus on artificial intelligence, statistics, and probability.

Their main fields of study include:

  • Computer Science (82 publications)
  • Mathematics (72 publications)

Within these fields, they have contributed extensively to subfields such as:

  • Artificial Intelligence (57 publications)
  • Statistics and Probability (51 publications)
  • Statistics, Probability and Uncertainty (24 publications)
  • Computational Theory and Mathematics (14 publications)
  • Statistical and Nonlinear Physics (11 publications)

Major topics covered in their research include:

  • Markov Chains and Monte Carlo Methods (64 publications)
  • Gaussian Processes and Bayesian Inference (48 publications)
  • Probabilistic and Robust Engineering Design (46 publications)
  • Statistical Methods and Inference (30 publications)
  • Target Tracking and Data Fusion in Sensor Networks (22 publications)
  • Model Reduction and Neural Networks (20 publications)
  • Advanced Multi-Objective Optimization Algorithms (18 publications)

Youssef M. Marzouk has published extensively, with frequent venue contributions including:

  • arXiv (Cornell University) - 60 publications
  • SIAM Journal on Scientific Computing - 5 publications
  • Mathematics of Computation - 2 publications
  • Journal of Computational Physics - 2 publications
  • Constructive Approximation - 2 publications

Some of their recent papers are:

  • Certified dimension reduction in nonlinear Bayesian inverse problems, 2022, Mathematics of Computation
  • Coupling Techniques for Nonlinear Ensemble Filtering, 2022, SIAM Review
  • Multifidelity Dimension Reduction via Active Subspaces, 2020, SIAM Journal on Scientific Computing
  • On the Representation and Learning of Monotone Triangular Transport Maps, 2023, Foundations of Computational Mathematics
  • Optimal experimental design: Formulations and computations, 2024, Acta Numerica

Frequent co-authors collaborating with Youssef M. Marzouk include:

  • Ricardo Baptista (15 and 13 co-authored papers)
  • Olivier Zahm (12 co-authored papers)
  • Fengyi Li (9 co-authored papers)
  • B. Zhang (7 co-authored papers)

Best Publications

  • Stochastic spectral methods for efficient Bayesian solution of inverse problems

    Youssef M. Marzouk;Habib N. Najm;Larry A. Rahn

  • Simulation-based optimal Bayesian experimental design for nonlinear systems

    Xun Huan;Youssef M. Marzouk

  • Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems

    Youssef M. Marzouk;Habib N. Najm

  • A stochastic collocation approach to Bayesian inference in inverse problems

    Youssef Marzouk;Dongbin Xiu

  • Bayesian inference with optimal maps

    Tarek A. El Moselhy;Youssef M. Marzouk

  • Data-driven model reduction for the Bayesian solution of inverse problems

    Tiangang Cui;Youssef M. Marzouk;Karen E. Willcox

  • Large-Scale Inverse Problems and Quantification of Uncertainty

    Lorenz Biegler;George Biros;Omar Nabih Ghattas;Matthias Heinkenschloss

  • Transport Map Accelerated Markov Chain Monte Carlo

    Matthew D. Parno;Youssef M. Marzouk

  • Dimension-independent likelihood-informed MCMC

    Tiangang Cui;Kody J.H. Law;Youssef M. Marzouk

  • Adaptive Smolyak Pseudospectral Approximations

    Patrick R. Conrad;Youssef M. Marzouk

  • Uncertainty quantification in chemical systems

    Habib N. Najm;Bert Debusschere;Youssef Marzouk;S. Widmer

  • Likelihood-informed dimension reduction for nonlinear inverse problems

    T Cui;J Martin;Y M Marzouk;A Solonen;A Solonen

  • Surrogate and reduced-order modeling: a comparison of approaches for large-scale statistical inverse problems [Chapter 7]

    M. Frangos;Y. Marzouk;K. Willcox;B. van Bloemen Waanders

  • Multifidelity importance sampling

    Benjamin Peherstorfer;Tiangang Cui;Youssef M Marzouk;Karen E Willcox

  • Optimal low-rank approximations of Bayesian linear inverse problems

    Alessio Spantini;Antti Solonen;Tiangang Cui;James Martin

  • Improved profile fitting and quantification of uncertainty in experimental measurements of impurity transport coefficients using Gaussian process regression

    Mark Alan Chilenski;Martin J. Greenwald;Youssef M. Marzouk;Nathaniel Thomas Howard

  • Sampling via Measure Transport: An Introduction

    Youssef Marzouk;Tarek Moselhy;Matthew Parno;Alessio Spantini

  • GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN

    Xun Huan;Youssef M. Marzouk

  • Spectral Tensor-Train Decomposition

    Daniele Bigoni;Allan Peter Engsig-Karup;Youssef M. Marzouk

  • Adaptive Construction of Surrogates for the Bayesian Solution of Inverse Problems

    Jinglai Li;Youssef M. Marzouk

  • Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

    Patrick R. Conrad;Youssef M. Marzouk;Natesh S. Pillai;Aaron Smith

  • A Stein variational Newton method

    Gianluca Detommaso;Tiangang Cui;Alessio Spantini;Youssef Marzouk

Frequent Co-Authors

Habib N. Najm
Habib N. Najm Sandia National Laboratories
Karen Willcox
Karen Willcox The University of Texas at Austin
Omar M. Knio
Omar M. Knio King Abdullah University of Science and Technology
Heikki Haario
Heikki Haario Lappeenranta University of Technology
Julien M. Hendrickx
Julien M. Hendrickx Université Catholique de Louvain
Omar Ghattas
Omar Ghattas The University of Texas at Austin
Michael L. Falk
Michael L. Falk Johns Hopkins University
Timothy P. Weihs
Timothy P. Weihs Johns Hopkins University

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