// modeling, simulation & analysis

Sedrick Bouknight

Simulation engineer focused on physics-based modeling, digital twins, and GPU-accelerated computing — bridging high-fidelity simulation with real-world system performance.
Strong interests in game technologies, spatial computing, physical AI, neural rendering, and robot learning.

View Projects Get in Touch
TUCSON, AZ · · RAYTHEON · MS&A ENG II
01

About

I'm a modeling, simulation & analysis engineer at Raytheon, working on scene generation, building high-fidelity synthetic EO/IR and RF environments that drive performance simulation for weapon systems. My work spans physically based rendering, GPU-accelerated algorithms, sensor simulation, and HIL/HPC integration.

Before that, I spent two years at Oak Ridge National Laboratory contributing to research & development for the United States Department of Energy (DOE). Specifically I worked on digital twins of Frontier, the world's first exascale supercomputer, and other international HPC systems. I developed interactive 3D visualization software in Unreal Engine and NVIDIA Omniverse, OpenUSD scene pipelines, real-time telemetry integration, and XR interfaces for HoloLens 2 and Apple Vision Pro. I also contributed to national security efforts and built 3D geospatial applications with CesiumJS and React to provide assistance to multiple states regarding data center feasibility and critical infrastructure analysis.

Domains

  • Modeling & Simulation
  • Digital Twins
  • Computer Graphics
  • XR & Visual Computing
  • Artificial Intelligence
  • HPC & Accelerated Computing
  • Robotics

Tools & Tech

  • C++ / Python / C#
  • NVIDIA Omniverse / OpenUSD
  • Unreal Engine / Unity
  • CUDA / OpenGL / Vulkan
  • React / CesiumJS
  • PyTorch / TensorFlow
02

Projects

C++ Python OpenUSD Omniverse

ExaDigiT

Open-source digital twin framework for exascale supercomputers, incorporating 3D assets, VR/AR capabilities, telemetry assimilation, power simulations, and cooling system control models. Partnered with Hewlett Packard Enterprise and NVIDIA. Won the 2025 R&D 100 Award.

exadigit.github.io →
C++ Vulkan Slang CMake

Sage

Standalone Vulkan 1.3 renderer and interactive scene editor featuring a bindless descriptor architecture, Cook-Torrance PBR shading, and an HDR pipeline with Reinhard/ACES tonemapping. Supports runtime glTF loading, procedural primitives, directional shadow mapping, and object-ID picking — built on dynamic rendering with no VkRenderPass and shaders compiled from Slang to SPIR-V.

GitHub →
C++ CUDA NVIDIA NSight

Accelerated Ray Tracer

Physically-based ray tracer with multi-sample anti-aliasing, depth-of-field via thin-lens camera, and PBR material models. Refactored from serial C++ to CUDA GPU execution — reduced render time for a sample scene from 5 hours to 30 seconds via NSight Compute profiling.

GitHub →
Python PyTorch OpenAI Gym

Doom Deep Q-Learning Agent

Deep Q-Learning agent trained to play Doom within the OpenAI Gym framework. Implements experience replay and reinforcement learning techniques to build a proficient game-playing policy from raw environment observations.

GitHub →
Python TensorFlow OpenCV

Deep Learning Facial Recognition

Real-time facial location, expression classification, and recognition pipeline. Applied transfer learning and hyperparameter tuning on open-source neural networks to exceed 75% accuracy across diverse recognition tasks.

GitHub →
03

Resume

// experience

Modeling Simulation & Analysis Engineer II

Raytheon  ·  Tucson, AZ

Feb 2026 — Present
  • Develop physics-based scene generation pipelines for synthetic sensor data and real-world phenomenology
  • Collaborate with SMEs to validate sensor fidelity and environmental realism across EO/IR/RF modalities
  • Develop GPU-accelerated graphics and simulation algorithms (OpenGL/CUDA) to support scene generation
  • Run Monte Carlo simulations on HPC grid to support weapon systems performance analysis at scale
  • Explore game engine technologies for synthetic data generation and AI/ML applications

Software Developer II

Oak Ridge National Laboratory  ·  Oak Ridge, TN

May 2025 — Feb 2026
  • Developed interactive 3D geospatial visualization and simulation tools using CesiumJS and React, enabling real-time analysis of datacenter feasibility and national energy infrastructure.
  • Designed a modular layer and rendering system supporting dynamic entities, contextual overlays, and scalable data pipelines mapping complex spatial datasets into responsive 3D environments.
  • Engineered full-stack, production-ready applications integrating backend services, REST APIs, and 3D frontend visualization.
  • Collaborated with multidisciplinary teams to transform research data and simulation outputs into interactive visual experiences supporting large-scale decision-making and infrastructure planning.

Software Developer I

Oak Ridge National Laboratory  ·  Oak Ridge, TN

Dec 2023 — May 2025
  • Implemented interactive digital twins of the Frontier supercomputer and other HPC systems using Unreal Engine C++ and NVIDIA Omniverse Kit extensions, integrating real-time telemetry with XR interfaces on HoloLens 2 and Apple Vision Pro.
  • Developed a custom USD generation library to automate data center scene construction — supporting variant sets, metadata organization, and rack-level modeling. Leveraged in both NVIDIA Omniverse and Blender workflows for scalable 3D scene authoring.
  • Built automation pipelines for large-scale OpenUSD scene composition, enabling procedural instancing, hierarchical scene traversal, and metadata-driven layout generation for digital twin environments.
  • Integrated thermofluid and power simulation models into a unified Python digital-twin framework, enabling system-level performance visualization and optimization.
  • Contributed to the ExaDigiT ecosystem via scene orchestration tools, runtime monitoring extensions, and XR data visualization modules to accelerate human–machine interaction in HPC operations.

Software Engineering Intern

Tech Core  ·  Tucson, AZ

Jun 2022 — Aug 2022
  • Developed immersive VR experiences focused on visualizing environmental effects on agriculture over time.
  • Imported 3D assets and Quixel Megascans; used Blueprint scripting and C++ in Unreal Engine for development on the Meta Quest 2.

// education

B.S. Applied Physics, Mathematics, Chemistry (Triple Major)

University of Arizona  ·  Minors: Computer Science, Economics

Aug 2018 — Dec 2022
  • Relevant coursework: Artificial Intelligence, Machine Learning, Neural Networks, Partial Differential Equations, Thermodynamics, Stochastic Processes, Numerical Methods, Data Structures & Algorithms, Computational Physics.

// publications

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Herron, E., Lama, V., Bouknight, S., Ghosal, T.

2026 ACM Computing Surveys (CSUR)  ·  May. 2026  ·  DOI: 10.1145/3815423

Implementing Immersive Analytics for Digital Twins in Data Centers

Dhakal, A., Prakash, P., Hong Enriquez, R. P., Dykes, T., Bouknight, S., et al.

2025 IEEE International Symposium on Emerging Metaverse (ISEMV)  ·  Honolulu, HI  ·  Oct. 2025  ·  DOI: 10.1109/ISEMV67326.2025.00024

A Digital Twin Framework for Liquid-Cooled Supercomputers as Demonstrated at Exascale

Brewer, W., Maiterth, M., Kumar, V., Wojda, R., Bouknight, S., et al.

SC'24 — International Conference for High Performance Computing  ·  Atlanta, GA  ·  Nov. 2024  ·  DOI: 10.1109/SC41406.2024.00029

Visualizing an Exascale Data Center Digital Twin: Considerations, Challenges and Opportunities

Maiterth, M., Brewer, W., De Wet, D., Greenwood, S., Kumar, V., Hines, J., Bouknight, S., et al.

2024 IEEE Visualization and Visual Analytics (VIS)  ·  St. Pete Beach, FL  ·  Oct. 2024  ·  DOI: 10.1109/VIS55277.2024.00012

Dynamic Modeling of Power Conversion Stages for an Exascale Supercomputer

Wojda, R. P., Maiterth, M., Bouknight, S., and Brewer, W.

2024 IEEE Energy Conversion Congress and Exposition (ECCE)  ·  Phoenix, AZ  ·  DOI: 10.1109/ECCE55643.2024.10861715

// awards & certifications

R&D 100 Award  ·  Software/Services Category

R&D World — ExaDigiT Digital Twin Framework, co-developed with Hewlett Packard Enterprise

2025

OpenUSD Development Certification

NVIDIA

2026

AI Professional Program

Stanford University School of Engineering

2025

Hands-on HPC Certification

Oak Ridge Leadership Computing Facility

2024

Certified AI Engineer

United States Artificial Intelligence Institute

2023
Download PDF
04

Contact

I'm open to conversations about simulation, autonomous systems, digital twins, visualization, or anything at the intersection of physics and AI.

sedrick@bouknight.io

01 LinkedIn 02 GitHub 03 Resume PDF