(+961) 1 421 000 ext 3372 rami.haddad@usj.edu.lb
Rami El Haddad is an Associate Professor of Mathematics at the Faculty of Science at Saint Joseph University of Beirut (USJ). From 2012 to 2019, he served as Chairperson of the Department of Mathematics, during which he established a Bachelors a Masters degree in Data Science. He currently coordinates the Master’s program in Actuarial Science Finance. Since May 2024, he serves as the Director of the Center of Statistics at the Vice-Rectorate for Research at USJ.
Highest degree : PhD in Mathematics - Université de Savoie - France
Degrees | University | Country | Year |
---|---|---|---|
Mathematics | Université de Savoie | France | 2008 |
Partial Differential Equations, Numerical Analysis | Saint Joseph University of Beirut | Lebanon | 2004 |
Pure Mathematics | Université Libanaise (UL) | Lebanon | 2003 |
Probability Computation
Probability for Data Science
Inductive Statistics
Integration Measure Theory
Probability Theory
Inferential Statistics
Stochastic Calculus
Experience in University Teaching Outside USJ | Country | Institution | Start Date | End Date |
---|---|---|---|---|
Part-time lecturer | Lebanon | American University of Beirut (AUB) | 07/06/2021 | |
Temporary Teaching and Research Associate | France | Université du Maine | 01/09/2007 | 31/08/2008 |
Part-time lecturer | France | Université de Savoie | 01/09/2006 | 31/08/2007 |
Professional Experience | Organization | Start date | End date |
---|---|---|---|
Visiting scholar (researcher) | Université de Lille | 18/09/2023 | 20/10/2023 |
Visiting scholar (researcher) | Université de Lille | 28/09/2021 | 19/12/2021 |
Engineering and Technology, Sciences
My research focuses on numerical probabilities stochastic simulations, with a particular interest in Monte Carlo methods. These methods are essential for solving complex problems in various fields such as finance, engineering, physical sciences by enabling precise estimations through random modeling and simulation techniques. My work contributes to the improvement of Monte Carlo algorithms, thereby optimizing their efficiency and applications.
1. L. Alsouki, L. Duval, C. Marteau, R. Haddad, F. Wahl. Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for feature selection prediction with tunable sparsity evaluation on simulated near-infrared (NIR) data. Chemometrics and Intelligent Laboratory Systems, Volume 237, (2023).
2. C. Lécot, P. L’Ecuyer, R. El Haddad, A. Tarhini. Quasi-Monte Carlo simulation of coagulation-fragmentation. Mathematics and Computers in Simulation, Volume 135, 5162 (2019).
3. R. Fakhereddine, R. El Haddad, C. Lécot, J. El Maalouf. Stratified Monte Carlo simulation of Markov chains. Mathematics and Computers in Simulation, Volume 135, 5162 (2017).
4. R. El Haddad, C. Lécot and G. Venkiteswaran. Diffusion in a nonhomogeneous medium: quasi-random walk on a lattice. Monte Carlo Methods and Applications, Volume 16, 211--230, (2010).
5. R. El Haddad, C. Lécot, P. LEcuyer, and N. Nassif. Quasi-Monte Carlo methods for Markov chains with continuous multi-dimensional state space. Mathematics and Computers in Simulation, Volume 81, 560--567, (2010).
h3>Formations et Certifications :
Achevés ou en cours : 5 projets
Nombre de participations : 13
Articles publiés : 13