Stochastic multiscale modeling and design of complex systems, with particular interest in granular materials, fluid dynamics, multi-agent systems and active matter.
Theoretical foundations and applications of scientific machine learning for discovering physical laws from observation data in complex and cyber-physical systems.
American University of Beirut - 2022
Henry J. Ramey, Jr. Fellowship Award
Stanford University - 2020
Frank G. Miller Fellowship Award
Stanford University - 2018
American University of Beirut
Winter 2022
Deep Learning for Fluid Dynamics
University of Washington
Spring 2021
Introduction to Multiphase Flow in Porous Media
American University of Beirut
Summer 2018
Applied Mathematics for Reservoir Engineering
Teaching Assistant at Stanford University
Winter 2017
Introduction to Uncertainty Quantification
Teaching Assistant at UC San Diego
Fall 2017
Introduction to Dynamics
Teaching Assistant at UC San Diego
Winter 2016
Dynamics and Control of Aircraft Vehicles
Teaching Assistant at UC San Diego
Winter 2015
Introduction to Music Technology
Teaching Assistant at UC San Diego
Summer 2015
Aircraft Engineering Design
Teaching Assistant at UC San Diego
Spring 2014
Seminar Organizer: 2020-2023
Data-driven Methods in Science and Engineering, AI Institute
Membership in:
American Physical Society (APS), Society of Industrial and Applied Mathematics (SIAM).
Reviewer at:
Journal of Machine Learning for Modeling and Computing, Journal of Computational Physics, AIP Physics of Fluids, Journal of Fluid Mechanics, Physica D: Nonlinear Phenomena, ComputerMethods in Applied Mechanics and Engineering.
deep-delay-autoencoder
Discovers high dimensional models from 1D data using deep delay autoencoders
bucki-data
Machine learning algorithms for discovering dimensionless groups from simulation and experimental data
granular-compaction
Monte Carlo 1D dynamic compaction of a two-phase multiscale granular material
NewsAndTime
Machine learning algorithm for predicting date of publication from content of news article
learning-pdf
Sparse identification of PDF equation and closure models based on Monte Carlo simulations
Socio-hydro-abm
Agent based simulations and control of socio-hydrological models
Gluvn
Sensor I/O and machine learning for Music glove instrumentMusic
My research interests
Stochastic multiscale modeling and design of complex systems, with particular interest in granular materials, fluid dynamics, multi-agent systems and active matter.
Theoretical foundations and applications of scientific machine learning for discovering physical laws from observation data in complex and cyber-physical systems.
Education
Ph.D. in Granular Materials, Advisor: Daniel Tartakovsky
Department of Energy Science and Engineering
Thesis: Stochastic multiscale modeling of complex materials
M.S. in Fluid Mechanics
Department of Mechanical and Aerospace Engineering
Thesis: Discrete-to-continuum modeling with reverse Brownian motion
B.Eng. in Mechanical Engineering
Department of Mechanical Engineering
Experience
Assistant Professor
Department of Mechanical Engineering, Artificial Intelligence Hub
Postdoctoral Fellow, AI Institute in Dynamic Systems, with S. Brunton & J. N. Kutz
- Data-driven discovery of nonlinear dynamics in complex systems
Earth and Environmental Sciences
- Computational agent based modeling for socio-hydrological simulations
Music Technology Lab
- Design, building and machine learning of a glove musical instrument
Aerosols Research Lab, with Alan L. Shihadeh
- Experimental data collection & analysis of water-pipe hookah toxicity studies
Swarm Lab
- Finless micro-rocket: Modeling, control, manufacturing of micro-rockets without fins
Microflows and Microscale Heat Transfer Lab, with Issam Lakkis
- Modeling and simulation of a lab-on-a-chip microfluidic transistor
- Vortex methods for slip boundary conditions
Speaker
- SIAM Mathematics of CSE, invited speaker | Amsterdam, NL - 2023
- University of Brasilia Mechanics Seminar, invited speaker | Virtual, Brasilia, Brazil - 2022
- Columbia University, LEAP ML Climate Journal Club, invited speaker | Virtual, Manhattan, NY - 2022
- Applied and Computational Mathematics Seminar, invited speaker | Tulane, LA - 2022
- AUB mechanical engineering seminar, invited talk | Beirut, Lebanon - 2022
- CWI Amsterdam seminar, invited speaker | Virtual, Amsterdam, NL - 2022
- SIAM Mathematics of Data Science, invited speaker |San Diego, CA - 2022
- MPML University of Lisbon, invited speaker | Lisbon, Portugal - 2022
- USNC for Ap. and Theoretical Mechanics, invited speaker | Austin, TX - 2022
- Oak Ridge National Lab workshop on AI for robust engineering | Oak Ridge, TN - 2022
- University of Southern California, invited speaker | Los Angeles, CA - 2022
- APS Division of Fluid Dynamics | Phoenix, AZ - 2021
- SIAM Annual Meeting | Virtual - 2021
- Carnegie Mellon University, invited Speaker Scientific Machine Learning | Virtual - 2021
- SIAM Computational Science and Engineering Conference | Virtual - 2021
- SIAM Computational Science and Engineering Conference | Spokane, WA - 2019
- Multiscale Modeling Workshop AFOSR | Eglin, FL - 2018
- Air Force Research Lab Annual Review | Washington D.C. - 2016
- SIAM Geosciences Conference | Stanford, CA - 2014