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I am a Ph.D. student at Cornell University studying Particle Physics for the CMS Experiment at CERN. My research focuses on high-performance and parallel computing applications for particle tracking, funded by Princeton's Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP). Outside of physics, I spent a year as a Research Engineer for a defense company near Washington DC writing software for research projects funded primarily by DARPA.

Current Projects:

  • Line Segment Tracking (LST): LST is a highly parallelizable algorithm written in C++ built to reconstruct tracks from particle collisions in the CMS detector at CERN. It aims to replace the current Kalman Filter-based algorithms with a new GPU-based approach to handle the increased volume of data expected from the High Luminosity Large Hadron Collider (HL-LHC).

Past Projects:

  • Light Dark Matter eXperiment (LDMX): LDMX is a proposed particle physics experiment led by a group at Stanford designed to search for low-mass dark matter. I developed the experiment's background rejection model with XGBoost while as an undergrad at UC Santa Barbara under Joe Incandela.
  • TracePy: TracePy is a sequential ray tracing package that I wrote in Python 3 for designing optical systems in the geometric optics regime. It features lens optimization from Scipy. I also developed a parallelizable version of TracePy written in C++ that is capable of running on GPU's.

Gavin Niendorf's Projects

maze icon maze

Maze environment for DRL generalization studies

snake icon snake

OpenAI's PPO baseline applied to the classic game of Snake

tracepy icon tracepy

Ray Tracing and Optical Design in Python

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