# Philippe Proctor > Software Engineer | Gamma Reality Inc. Location: San Francisco, California, United States Profile: https://flows.cv/philippeproctor M.Sc. in Machine Learning and Signal Processing with experience in the application and development of deep reinforcement learning, statistical signal processing, and machine learning algorithms to solve complex problems. I am excited to continue learning and applying these techniques to new domains. ## Work Experience ### Software Engineer @ Gamma Reality Inc. Jan 2021 – Present | Richmond, California, United States • Delivered phase I SBIR contract for autonomous robotic radiation surveying. This utilized a graph transformer model and reinforcement learning to enable LAMP system navigation and source seeking in unknown environments • Led full-stack development of detector API, from low-level C++ readout firmware to React-based operator interface • Led design and launch of nuclear power plant data management platform, automating compliance reporting workflows • Architected ROS-based sensor package that integrates data from multiple dosimeter types, enhancing LAMP system's radiation measurement accuracy and expanding addressable market segments • Serve as technical lead for flagship commercial product, debugging production issues, and implementing 10 critical feature enhancements • Engineered automated calibration tool for detector systems that reduced pre-shipment QA time by 5 hrs/system ensuring measurement accuracy across deployed units ### Graduate Research Assistant @ Portland State University Jan 2019 – Jan 2021 | Teuscher Lab • Thesis: Proximal Policy Optimization for Radiation Source Search • First author on paper, in collaboration with another research university • Constructed novel deep reinforcement learning architecture in Python / Pytorch that achieved a success rate of 95% in a complex nuclear source search task outperforming gradient search by 68% • Built OpenAI Gym radiation simulation environment that used a visibility graph for shortest path calculation with polygonal obstructions • Implemented information-theoretic control algorithm from the literature that utilized a Bayesian particle filter for the radiation source search comparison. • Mentored 3 NSF-funded undergraduate students on computational modeling research projects and ran lab meetings for 15 students • Presented research results and project progress at 2 annual reviews for funding agency ### Undergraduate Research Assistant - Biomedical Signal Processing Lab @ Portland State University Jan 2018 – Jan 2019 | Portland State • Collected and analyzed data gathered from radio-frequency sensor mesh networks • Added parsing functionality to MotioSens system in MATLAB to improve data readout capabilities ### Instrument Test Engineer Intern @ Medical MicroInstruments SpA Jan 2018 – Jan 2018 | Calci, Italy • Designed instrument life cycle test protocol in MATLAB for main operational unit that revealed mechanical design flaw resulting in component redesign that increased instrument lifespan by 9% • Soldered and tested printed circuit boards used in the robot control system ### Data Analyst Intern @ Carpe Data Jan 2016 – Jan 2017 | Santa Barbara, California Area • Created data cleaning script in Python using Pandas to remove duplicates and flag feature input errors, used in an exploratory data analysis to assess efficacy of potential company asset • Presented investigative report of company asset performance to management leading to integration of asset into product pipeline • Proposed 2 novel data sources for use in the predictive modeling ## Education ### Master's degree in Electrical and Electronics Engineering Portland State University ### Biopsychology in Biology/Biological Sciences, General UC Santa Barbara ## Contact & Social - LinkedIn: https://linkedin.com/in/peproctor - Portfolio: https://peproctor.github.io/ --- Source: https://flows.cv/philippeproctor JSON Resume: https://flows.cv/philippeproctor/resume.json Last updated: 2026-03-29