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My background is in physics, software development, and AI systems, with applications in automation, optimization, and data science.
These are the major topics I have encountered either professionally, recreationally, or academically:
- Building Agent Frameworks and Automating Complex Workflows in Physics
- Creating Comprehensive Python Libraries for Data Engineering (datamesh, dataproducts)
- Data Science & Management in Financial Technology
- Quantum Monte Carlo Particle Simulations and Machine Learning in Nuclear Physics
- Master's Thesis: Effective Mass and Machine Learning in Strongly Interacting Neutron Matter
- 2021: Machine-learning approach to finite-size effects in systems with strongly interacting fermions
- 2020: Neutron matter at the interface(s): Static response and effective mass
- 2019: Non-perturbative Extraction of the Effective Mass in Neutron Matter
- 2017: Exploring finite-size effects in strongly correlated systems
- Reinforcement Learning in Simulated Robots (C++/OpenGL Engine)
- Game Theory and Player-Decision Optimization (osrsmath)
- Python & Device Automation Software (pybiosis)
- Tutoring & Lecturing in STEM (high-school, college, university)
- Dashboards & Home Automation Software
- Graphs and Network Analysis
I am eager and open to exploring potential opportunities.
For professional inquiries, you may view LinkedIn.
For anything else you can check out the Contact Page.