I am a Computational Biophysics PhD student at the University of California, Riverside (UCR) in Dr. Giulia Palermo’s Lab, working at the interface of molecular simulations, machine learning, and CRISPR gene editing.
My work focuses on building AI-driven molecular simulation pipelines, particularly graph neural networks (GNNs) and enhanced sampling tools, to study prime editing mechanisms.

• Machine Learning for Molecular Simulation
  Graph Neural Networks (GNNs), attention mechanisms, VAMP/VAMPnet, TICA, MSMs, collective variable discovery.
• CRISPR–Cas Systems & Gene Editing
  Structural + dynamical analysis of prime editing complexes across the full edit cycle.
• High-Performance Computing (HPC)
  Large-scale MD (Amber, GROMACS, NAMD), parallel workflows, cluster automation.
• Biomolecular Mechanisms
  Reaction pathways, pathway flux (TPT), conformational landscapes.

Molecular Simulation: Amber 19/24, GROMACS 2022–2025, NAMD 2.14/3.0, PLUMED 2.9, ORCA, Modeller, VMD, PyMOL
Machine Learning / Data: PyTorch Geometric, PyTorch, scikit-learn, MDAnalysis, NumPy/Pandas
HPC Tooling: Slurm, job arrays, MPI, CUDA 10.1–12.8, cluster automation, rsync
Scripting: Python, Bash, MATLAB
Workflow Tools: Git, Conda, VS Code SSH, tmux, Linux (Rocky8/CentOS/Ubuntu)

I’m looking to collaborate on projects involving:

• Deep neural networks for biochemical mechanism discovery
• AI for molecular dynamics & conformational analysis
• CRISPR-focused molecular simulations
• High-performance bio-computing workflows

If your work intersects with these, let’s talk!

Photography • Music • Weightlifting • Hiking • Travel

• Twitter: @lrodrz1
• Blog: https://lrodrz.github.io
• Email: lrodr747 ./. gmail ./. com