Postdoctoral Fellow @ Brookhaven National Laboratory Physicist & AI/ML Aficionado specializing in Particle Physics Simulations & HPC Infrastructure
I currently serve as a Co-convener for the Physics and Detector Simulation Working Group and the Simulation Productions Working Group for the ePIC detector collaboration.
- Large-Scale Computing: Deploying automated workflows on the Open Science Grid, processing ~150 core years to generate ~150TB of physics data monthly.
- AI/ML in Physics: Applying Neural Networks for momentum reconstruction and Bayesian Optimization (scikit-learn) for detector geometry.
- GPU Acceleration: Developing GPU-accelerated simulations using Celeritas and NVIDIA OptiX to optimize electromagnetic and optical photon tracking.
| Category | Tools & Technologies |
|---|---|
| Languages | Python C++ Bash |
| Physics/Sim | GEANT4 DD4hep ROOT ACTS Celeritas EIC-Opticks |
| ML & Data | Neural Networks Bayesian Optimization Scikit-learn Pandas |
| Infrastructure | HPC/HTC Open Science Grid Docker HTCondor SLURM |
| Workflow/DevOps | CI/CD Pipelines Spack Snakemake PanDA WMS Git |
- Ph.D. in Particle Physics | University of Manitoba (2022)
- B.Sc. Joint Honors (Physics & Math) | University of Manitoba (2015)
- BNL Mini I-Corps Program: Exploring commercialization of NVIDIA OptiX-based frameworks for optical photon tracking.
- BNL Entrepreneurship Program: Validating value propositions for sub-picosecond timing synchronization.
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