John Matter

BS Physics, UC Davis (2012)
PhD Physics, University of Virginia (2021)

contact: jmatter4 at gmail

github
linkedin

I am a nuclear physicist seeking employment as a data scientist or software engineer.

Bio

I received my BS in physics from UC Davis in 2012. For my senior honors thesis, I studied the domain wall fermion implementation of chiral fermions in lattice gauge theory under the guidance of Professor Joe Kiskis. After graduating, I worked with Professor Marjorie Solomon at the UC Davis MIND Institute using fMRI to study higher cognition in Autism Spectrum Disorder.

I completed my PhD in physics at the University of Virginia in 2021. My research under Professor Nilanga Liyanage, Professor Krishni Wijesooriya, and Professor Dipangkar Dutta can be divided into three categories:

  • Particle-tracking systems for accelerator-based nuclear physics experiments
  • Imaging technologies and analysis to improve gamma radiation therapy for lung and soft tissue tumors
  • Nuclear/nucleon structure and interactions

In 2022, I began working as a Research Scientist at Meta on the Transparent Ads Experience team. Our team works to help users, advertisers, and regulators better understand the ways Meta uses large data sets and machine learning to serve ads. My work on the team includes building and maintaining data processing pipelines, developing user surveys, and performing experiments to improve our the algorithms and models we use to explain Meta’s ad ranking systems.

PhD Dissertation

Color transparency is a phenomenon in which interactions between the nuclear medium and particles like protons are attenuated. My dissertation experiment used a beam of high energy electrons to knock protons out of carbon nuclei in order to study color transparency. You can read a description of the experiment here.

Skills

  • Programming/scripting languages: C/C++, Python, bash
  • Data analysis/visualization: MATLAB, R, ggplot, matplotlib, scipy, numpy, pandas, sklearn, ROOT
  • Public speaking to specialist and non-specialist audiences
  • Technical writing/documentation
  • Soldering
  • CAD

Hobbies

  • DIY electronics
  • Modular synthesizers
  • Computer music (Max/MSP, Supercollider)
  • Bread baking