My research has involved both experimental and theoretical work in astrophysics and particle physics:

• Analyzed data from the POLARBEAR telescope to search for evidence of dark matter. Lead author on a publication from a 50 person collaboration. Work involved likelihood analysis, statistics, and parallel computing on a supercomputer at NERSC.

• Helped build and validate a telescope to study the Cosmic Microwave Background as part of the Simons Observatory. Telescope operates with 10,000 superconducting detectors cooled to 0.1 Kelvin. Extensive work with cryogenic technology, low-noise cryogenic RF electronics, CAD and machine shop work, and device characterization and analysis in python. Lead the design of large structures to block thermal emission and supervised a $750,000 construction contract with a Chilean company. Within a 300 person collaboration: extensive presentation experience, led design reviews, failure analysis, documentation, peer-reviewed code and git workflow.

• Studied how a hypothetical dark matter candidate, sterile neutrinos, could be produced in the very early universe. Developed python code to compute sterile neutrino production rates.

I was the Lead Teaching Assistant for the laboratory course Physics 2CL, responsible for managing up to 10 fellow graduate student TAs and 300 undergraduate students, setting up labs, and developing lab manuals and exams. I have nine quarters of teaching experience.

I was awarded a short-term grant by the German Academic Exchange Service (DAAD) to study how a hypothetical dark matter candidate, sterile neutrinos, could be produced in the very early universe.

I built a neural network (python/tensorflow) to identify a particular type of particle, B mesons, in the LHCb experiment at the Large Hadron Collider.