My Research Interests

Research Interests

I am a physicist and computational neuroscientist working at the intersection of computational neuroscience, artificial neural network design, physics‑based simulation. I am currently working as a Computational Neuroscientist at The Biological Computing Co. (TBC). At TBC, we are running experiments in our wetlab in order to derive biological insights into software and hardware that can learn, adapt, and ultimately compute at a fraction of the time and energy cost of conventional silicon AI models. My broader interests span data‑driven modeling of biological neurons, complex dynamical systems, and finding novel methods of computation with greater capability and lower time and energy costs.

Education

Experience

Computational Neuroscientist — The Biological Computing Co. (TBC) (Aug 2025 – Present)

Research focused on investigating biological neurons as a foundation for next‑generation AI. I am a member of TBC’s computational neuroscience team, while also contributing to work in the AI model and ML algorithm space, bridging neural data and analysis with the design of biologically inspired models and architectures. TBC’s research program studies how biological neuronal cultures process information and translates those biologically derived principles into new AI models and architectures beyond transformers. Target application areas include computer vision and broader AI‑infrastructure improvements, with ongoing exploration of real‑time biological compute and pattern completion/prediction for time‑series data.

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.
• Biological‑Neuron Computing (TBC): Computational neuroscience research investigating biological neurons, toward better AI models and computing systems - see The Biological Computing Co..
• 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

• Email: lawson@lawsonfuller.com
• GitHub: https://github.com/LLFuller
• LinkedIn: https://linkedin.com/in/lawson-fuller-2ba627123

Last updated: May 2026