I'm a computational scientist specializing in Scientific Machine Learning (SciML), Molecular Dynamics, and High-Performance Computing. Currently based in Mons, Belgium 🇧🇪, I develop scalable computational workflows that bridge physics, chemistry, and machine learning to solve complex problems in materials science and beyond.

• Scientific ML & AI: Developing machine learning interatomic potentials (NequIP, Allegro) for nanoscale simulations
• Molecular Dynamics: Large-scale MD simulations investigating 2D materials, moiré superlattices, and emergent phenomena
• High-Performance Computing: Optimizing parallel workflows for massive-scale simulations on HPC clusters
• Multiscale Modeling: Connecting quantum mechanics (DFT) to classical simulations for materials design

• Ph.D. in Materials Science | University of Southern California (2025)
• M.S. in Computer Science | University of Southern California (2025)
• M.S. in Materials Engineering | University of Southern California (2025)
• B.S. in Physics (Highest Honors) + B.A. in Mathematics (Honors) | UC Santa Cruz (2018)

Python toolkit for generating periodic multi-layer moiré supercells with customizable twist angles for MD/DFT workflows. Accelerated with Numba and multiprocessing for rapid structure generation. (Repository in preparation)

Led a team to build a CV pipeline using YOLOv8 for player/ball tracking and LSTM-based trajectory prediction from video feeds. Demonstrates versatility in applying ML across domains.

Custom parallel post-processing scripts for analyzing massive MD trajectories, enabling rapid parameter sweeps across complex configurations.

Core contributor: Python modules for estimating photoluminescence line shapes from defects in 2D materials, bridging theory and experiment.

Languages & Tools:

Python (NumPy, Pandas, Numba, Multiprocessing) | Mathematica | LaTeX | Shell Scripting

ML/AI Frameworks:

PyTorch | TensorFlow | Graph Neural Networks | NequIP/Allegro | YOLOv8 | LSTM

Scientific Computing:

LAMMPS | VASP | Quantum ESPRESSO | Molecular Dynamics | DFT

HPC & Engineering:

Git | Linux/Unix | SLURM | Parallel Computing | System Integration

• Aditya, A., et al. "Emerging Ferroelectric Domains: Stacking and Rotational Landscape of MoS₂ Moiré Bilayers." ACS Nano (In Press, 2026)
• Irie, A., Aditya, A., et al. "Thermoelectric Grain Boundary in Monolayer MoS₂." J. Phys. Chem. C (2024)
• Aditya, A., et al. "Wrinkles, Ridges, Miura-Ori, and Moiré Patterns in MoSe₂ Using Neural Networks." J. Phys. Chem. Lett. (2023)
• Linker, T., Aditya, A., et al. "Exploring Far-from-Equilibrium Ultrafast Polarization Control in Ferroelectric Oxides." Science Advances (2022)

📄 Full publication list

• Advanced GNN architectures for materials property prediction
• French (living in Wallonia, Belgium!)
• Multiscale modeling techniques for hybrid nanomaterials

• 💼 LinkedIn
• 📧 anikeya9@gmail.com
• 🌍 Based in Mons, Belgium

"Translating complex physics into computational solutions, one simulation at a time."