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Youssef Diouane
M. Eng., M. Sc., Ph. D, HDR
  Publications
Assistant Professor
Department of Mathematical and Industrial Engineering
Phone: (514) 340-4711 Ext. 3865 Fax: (514) 340-4086 Room: A-520.15
Areas of expertise
Operations research and management science Algorithms Optimization Numerical analysis Optimization and optimal control theory
ORCID ResearchGate Google Scholar

Research interests and affiliations

Research interests
  • Numerical Optimization
  • Data Science and Machine Learning
  • Computational Science and Engineering
Expertise type(s) (NSERC subjects)
  • 1601 Operations research and management science
  • 2713 Algorithms
  • 2715 Optimization
  • 2955 Numerical analysis
  • 2956 Optimization and optimal control theory

Publications

Featured
Conference paper
Diouane, Y., Lucchi, A. & Patil, V. (2022). A globally convergent evolutionary strategy for stochastic constrained optimization with applications to reinforcement learning. Paper presented at the 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022) (pp. 836-859). Retrieved from https://proceedings.mlr.press/v151/diouane22a.html
Journal article
Diouane, Y., Picheny, V., Riche, R.L. & Perrotolo, A.S.D. (2022). TREGO: a trust-region framework for efficient global optimization. Journal of Global Optimization, 23 pages. Retrieved from https://doi.org/10.1007/s10898-022-01245-w
Journal article
Bergou, E.H., Diouane, Y., Kungurtsev, V. & Royer, C.W. (2022). A Stochastic Levenberg--Marquardt Method Using Random Models with Complexity Results. SIAM/ASA Journal on Uncertainty Quantification, 10(1), 507-536. Retrieved from https://doi.org/10.1137/20m1366253
Journal article
Bergou, E.H., Diouane, Y. & Kungurtsev, V. (2020). Convergence and Complexity Analysis of a Levenberg–Marquardt Algorithm for Inverse Problems. Journal of Optimization Theory and Applications, 185(3), 927-944. Retrieved from https://doi.org/10.1007/s10957-020-01666-1
Journal article
Priem, R., Bartoli, N., Diouane, Y. & Sgueglia, A. (2020). Upper trust bound feasibility criterion for mixed constrained Bayesian optimization with application to aircraft design. Aerospace Science and Technology, 105, 24 pages. Retrieved from https://doi.org/10.1016/j.ast.2020.105980
Conference paper
Saves, P., Bartoli, N., Diouane, Y., Lefebvre, T., Morlier, J., David, C., Nguyen Van, E. & Defoort, S. (2022). Multidisciplinary design optimization with mixed categorical variables for aircraft design. Paper presented at the AIAA SCITECH 2022 Forum, San Diego, CA, USA. Retrieved from https://doi.org/10.2514/6.2022-0082
See all publications (33)

Biography

Youssef Diouane is a professor at the department of Mathematics and Industrial Engineering (MAGI) of Polytechnique Montréal, Canada, effective February 1, 2022. Before joining MAGI, Prof. Diouane was a professor in the department of Complex Systems and Engineering (DISC) at ISAE-SUPAERO,Toulouse, France.

His research is concerned with using numerical optimization and its applications to complex systems, design and data sciences. He targets to develop and provide efficient optimization algorithms with optimal guarantees to solve optimization problems arising in engineering applications.