About Me
I am planning to graduate in Spring 2025 and am looking for full-time opportunities. Reach out to me if you have any relevant positions!
I am currently pursuing a Ph.D. in Physics at the University of Maryland Baltimore County (UMBC), specializing in computational materials science under the supervision of Dr. Can Ataca. I completed my M.S. in Physics at UMBC in 2021. I also hold a B.Sc. degree in Mechanical Power Engineering (Thermal Engines, Fluid/Gas Dynamics) from Menoufia University in Egypt, which I obtained in 2016.
Research Interests
My research interests lie at the intersection of condensed matter physics, materials science, chemistry, machine learning, and mathematics. Broadly, I am interested in integrating AI/data science techniques with multiscale atomistic simulations (MD, Enhanced sampling, MC, KMC, NAMD) and quantum-mechanical calculations (DFT, DFPT, DFTB, TDDFT, GW/BSE, QMC) to predict crystal structures, predict electronic-structure properties, and study physical/chemical phenomena at extensive length/time scales that emulate experimental reality.
I am also engaged in designing computational workflows to facilitate multiscale simulations and the machine learning of material properties.
I am currently also interested in the multiscale modeling of non-equilibrium atomistic dynamics in nanoscale devices under external stimuli, excited chemical/physical processes under light/electron/ion beams, and novel material synthesis methodologies.
Technical Skills
| Category | Technologies |
|---|---|
| Materials Simulation | DFT: VASP, Quantum ESPRESSO, GPAW, DFTB+, SIESTA/TranSiesta MD/MC: LAMMPS, ASE, JAX MD, Ovito Machine Learning Potentials: n2p2, GAP, SchNetPack, MACE, NequIP/Allegro Python Materials IDEs: ASE, pymatgen, pyiron Cluster Expansion: ATAT, icet QMC: QMCPACK |
| Programming Skills | Languages: Python, C++, FORTRAN, MATLAB ML/AI Frameworks: TensorFlow, PyTorch, JAX, PyTorch Geometric, e3nn |
Recent News
| Date | Details |
|---|---|
| March 2025 | Paper alert: Our latest paper, “Quantum Monte Carlo and Density Functional Theory Study of Strain and Magnetism in 2D 1T-VSe2 with Charge Density Wave States” (ACS Nano) is now published in ACS Nano. |
| Aug 2024 | Internship completion: Completed a summer internship at Samsung Semiconductor’s Advanced Materials Lab in Cambridge, MA, under the guidance of Dr. Yongwoo Shin. I developed a Python package for hybrid KMC/MD simulations within ASE to model the growth of amorphous boron nitride using neural network potentials, and benchmarked the results against TEM experiments. |
| Jul 2024 | Paper alert: Our latest paper, “Prediction of Frequency-Dependent Optical Spectrum for Solid Materials: A Multioutput and Multifidelity Machine Learning Approach” (ACS Applied Materials & Interfaces) is now published in ACS Applied Materials & Interfaces. |
| Feb 2024 | Conference alert: Presented a poster, “DFT+U Study of Magnetic Properties of Multiferroic NiI₂ Monolayers” at the NIST QMMS workshop. |
| Jan 2024 | Paper alert: Our paper, “Modeling Chemical Exfoliation of Non-van der Waals Chromium Sulfides by Machine Learning Interatomic Potentials and Monte Carlo Simulations” (The Journal of Physical Chemistry C) is now published in the Journal of Physical Chemistry C, in the virtual special issue “Machine Learning in Physical Chemistry Volume 2.” |