Lawson Fuller, Ph.D.

Lawson Fuller, Ph.D.

he/him

A physicist interested in studying novel computational methods through the lens of physics and neuroscience.

My Research Interests

Research Interests

I am a computational physicist working at the intersection of physics‑based simulation, computational neuroscience, and machine learning. My projects range from electromagnetic simulation, to graphs of interacting dynamical systems, to data‑driven modeling of biological neurons. I’m most interested in finding novel methods of computation using any available physical systems in order to create future computational technologies with greater ability and lower time and energy costs.

Education

DegreeInstitutionYearHighlights
Ph.D. Physics, with Specialization in Computational NeuroscienceUC San DiegoDec 2024Physics–ML hybrid modeling for neural dynamics; Bhadra Fellow 2023
B.S. Physics & Applied MathematicsUniversity of Arizona2018Undergraduate research in computational physics (relating to particle physics and black holes)

Experience

Computational Physicist — Imagia (Jun 2024 – Jul 2025)

Developed an end‑to‑end Python pipeline for electromagnetic design, cutting setup time from 8 h to ≈ 100 s (300x speedup), performed pre-processing and analysis of experimental image data, and coordinated across all simulation/design, fabrication, and experimental/analysis teams.

AI Scientist (Contractor) — Ascend OS (Feb 2025 – Apr 2025)

Architected an agentic LLM backend workflow that generated personalized ice‑breaker content for a 100‑person corporate event. Implemented pair-specific person-to-person LLM agent-facilitated introductions.

Research Assistant Intern — Lawrence Berkeley National Lab (Aug 2017 – Mar 2018)

Implemented C++ ROOT analyses for ATLAS collaboration; built Python visualization tools for the Particle Data Group and was credited in the Review of Particle Physics 2018.

Publications & Projects

  • Journal Article: “Reduced‑Dimension, Biophysical Neuron Models Constructed From Observed Data.” Neural Computation 34(7): 1545 – 1587 (2022).
    — see Paper in Neural Computation.
  • Low‑Power Neuromorphic Circuits: Ongoing collaborative project exploring circuits for robotics problems.
  • FDTD (Yee lattice) Solver: Parallelized electromagnetic solver from scratch with visualization scripts — see GitHub Repo: Optics_Sims.
  • MEEP HPC Integration: Wrapper scripts enabling multi‑core MEEP runs for optical metasurface pillar cells.

Teaching & Mentorship

  • Graduate TA, UC San Diego (2018 – 2024): Courses in neurophysics, scientific computing (MPI/OpenMP/CUDA), electromagnetism, thermodynamics, fluid mechanics, Newtonian mechanics, and nonlinear dynamics.
  • Mentored undergraduate researchers on spiking biological neural networks, physics simulation, and time-delay embedding modeling.

Contact

Last updated: July 2025