I'm a computational scientist, interested in discovering the simple rules that animate our complex universe using artificial — and sometimes natural — intelligence. My research is broadly driven by fundamental questions concerning the behavior of complex systems: like granular materials, fluids, brains, and social organisms.
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
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.
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.
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
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