Colby Lemon

Computational Physicist

https://lemonlab.net · https://github.com/lem-n

https://www.linkedin.com/in/colbylemon · colby@lemonlab.net · 214-587-8663

Profile

Computational physicist with two decades of experience building large-scale numerical models of complex physical systems. Deep expertise in PDE solvers, parallel computing (MPI, OpenMP, CUDA), and production scientific software in C++, Fortran, Python, and Julia. Proven track record of accelerating core solvers, modernizing legacy codebases, and coupling multi-physics simulations for spacecraft charging, magnetospheric dynamics, and plasma instrumentation. Currently extending into scientific machine learning — physics-informed neural networks, neural operator surrogates, and differentiable simulation — bridging traditional HPC methods with modern ML-accelerated workflows.

Core Skills

• Programming Languages: C++, Fortran, Python, Julia, Lua, Shell scripting
• Parallel & GPU Computing: MPI, OpenMP, CUDA, CuPy, Slurm
• Numerical Methods & Libraries: FEM/FEA, AMR, libMesh, PETSc, Trilinos, Kokkos
• Scientific Computing: PDE solvers, CFD, MHD, plasma simulation, mathematical optimization
• ML & Scientific ML: PyTorch, SciML (actively building depth in PINNs and neural operators)
• Performance Engineering: Profiling and bottleneck analysis, memory optimization, CPU/GPU architecture
• Data & Visualization: NumPy, SciPy, HDF5, Pandas, Matplotlib
• Software Engineering: Git, CMake/Make, modular design, test-driven development

Experience

The Aerospace Corporation · Space Science Applications Laboratory

El Segundo, California · 2005–Present

Three concurrent and overlapping technical roles spanning spacecraft charging simulation, magnetospheric modeling, and plasma instrument development.

Spacecraft Charging and Electrostatic Discharge Simulation

• Developed a 3D multi-physics model in C++ coupling Geant4 radiation transport with a finite-element Poisson solver and Ohm’s-law charge transport algorithm to simulate deep dielectric charging in spacecraft materials.
• Implemented adaptive mesh refinement to resolve localized charge accumulation and electric field gradients near material interfaces.
• Parallelized radiation transport with MPI and the electric field solver with MPI + PETSc.
• Built a 1D Python charging model for rapid-turnaround simulation of 10–15 year missions, supporting on-orbit anomaly investigations and ESD failure analysis.
• Benchmarked dense and sparse matrix solvers (NumPy, SciPy, CuPy, PyTorch) for the 1D Poisson equation on high-resolution grids to identify optimal solver strategies.
• Developed a Python-driven parametric simulation framework to sweep material properties and radiation environments, enabling systematic ESD susceptibility mapping across mission-relevant conditions.
• Performed pre-launch charging susceptibility analyses for payloads, solar arrays, and other components to estimate ESD risk to critical flight systems.

Magnetospheric Dynamics Modeling

• Developed a coupled magnetosphere–ionosphere–plasmasphere transport model for simulating space weather, magnetic storms, and auroral dynamics.
• Validated model predictions against satellite measurements to quantify accuracy and isolate the contributions of specific physical processes.
• Designed numerical experiments mapping cause-and-effect relationships between solar wind drivers and magnetospheric response.
• Optimized serial performance and parallelized advection and magnetic field solvers using OpenMP, reducing wall-clock time by over 100x on shared-memory systems
• Evaluated advection solver flux limiters to balance numerical diffusion against spurious oscillations in the plasma transport equations.
• Refactored legacy Fortran codebase using test-driven development; wrapped compiled Fortran with Julia to accelerate development/testing cycles; migrated significant portions to Modern Fortran and Python.
• Developed a relativistic Lorentz-force particle tracer in MPI Fortran to compute electron trajectories in 3D electromagnetic fields.
• Performed statistical analyses of satellite plasma and energetic particle data for process studies, model input generation, model validation, and satellite anomaly assessment (Python, NumPy, SciPy, Pandas, Matplotlib).

Plasma Instrument Design and Field Campaigns

• Supported four suborbital NASA sounding rocket missions: led payload-instrument integration, monitored ground-support equipment pre-flight and in-flight, and verified instrument performance.
• Designed, prototyped, fabricated, and launched a magnetic mass spectrometer for measuring plasma ion composition; flew on two sounding rockets to measure ions in the upper ionosphere and lower magnetosphere.
• Built a first-principles ion optics simulation coupling magnetic field geometry with an electric field solver to optimize electrode shapes compensating for field non-uniformities.
• Simulated electron and ion trajectories in CubeSat plasma-analyzer instruments to optimize performance metrics and maximize science return.

Education

• Ph.D., Physics — Rice University
  • Dissertation: “Simulating the Driven Magnetosphere”
• M.S., Astrophysics — Rice University
• B.S., Physics — University of Texas at Dallas
  • Additional coursework: Chemistry (5 courses), Computer Science (6 courses), Mathematics (9 courses)