Hello there!

I'm a computational chemist with expertise in machine-learned interatomic potential models. My work focuses on implementing AI solutions to challenging problems in chemistry, particularly in ensemble-based uncertainty, the atomic behavior of neural network potentials, and their applications in large-scale molecular simulations and reaction pathway discovery.

• ani-mm: ani-mm - OpenMM dynamics runner using public ANI potential models, includes live GUI viewer and CLI utilities
• mini-LLMs: LLMini — compact GPT-style transformer models trained on TinyShakespeare and WikiText datasets.
• C++ project: cpp-rng-simulator — modular C++ project demonstrating random sampling and RNG algorithms.
• Games / graphics: Mythic-Depths — procedurally generated Python dungeon crawler RPG built with PyGame.

• ANI Developer in the Roitberg Group

  • Development of generalized, transferable neural network potentials for approximating quantum chemical computations.
  • Investigating trends in predicted atomic energies and forces to improve model accuracy.
  • Expanding the ANAKIN-ME (Accurate NeurAl networK engINe for Molecular Energies) software package with predictive uncertainty quantification and analysis.
  • Uncertainty-based substructure sampling with LUKE: Use the Forces.

• Large-Scale Reactive Simulations

  • Simulating and analyzing the molecular dynamics of millions of atoms, identifying novel compounds and reaction pathways in Early Earth systems.
  • Developing advanced tools and workflows for big data analysis in molecular simulations.

• ML in Chemistry: Deep neural potentials, ensemble uncertainty, predictive modeling.
• Simulation Analysis: Large-scale MD, fragment identification, reaction pathway mapping.
• Big Data Management: CuDF, Dask, and NetworkX/CuGraph for analyzing 100 TB+ trajectory datasets.
• Software Development: Python, CUDA, Bash, HPC optimization, open-source contributions.
• Source Control Git/GitHub workflows, feature branching, code review.
• Visualization: VMD, PyMOL, Matplotlib, Seaborn, Plotly

• Early Earth Hero Run Simulation

  • Reactive molecular dynamics simulations on the scale of 10⁷ atoms using ANI potentials via a LAMMPS interface.
  • Scaling simulation and analysis workflows to benchmark HiPerGator's supercomputing infrastructure.

• Graph-Based Molecular Discovery

  • Detection millions of novel molecular conformations, including amino acids, dipeptides, sugars, and other prebiotic molecules.
  • Expanding graph-search algorithms to identify novel compounds from large-scale, ML-driven molecular dynamics simulations
  • Automating detection of reaction networks from large-scale reactive simulations.

• LUKE: Use the Forces

  • ANI model ensemble uncertainty-based conformational searching
  • Select localized atomic environments from highly uncertain atomic force predictions

I am a passionate open-source contributor! Some of my projects include:

• TorchANI - Neural network potentials; accurate quantum chemical predictions at ~10⁶ times speedup.
• Big Early Earth Analysis - Open pipelines for large-scale molecular dynamics trajectory analysis.
• LUKE: Use the Forces - (Pre-release) Package for predictive uncertainty-based data sampling with ANI models.

• Astronomy

  • I enjoy setting up my telescope on clear nights to watch the stars, and would consider myself an amateur astronomer
  • Did some undergraduate research on a binary star system in the Cygnus constellation
  • Would love to create a setup to start image collection and processing at home

• Video Games

  • Who would be surprised that someone who loves simulations of physics has an interest in video games...
  • Since I was a kid I have thought that the physics engines in video games are fascinating, and largely attribute my career choices to my interest in gaming.