gniendorf/ldmx-sw

LDMX C++ Framework

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.