Summary
Nathan Hewitt is a robotics software engineer with eight years of experience building learning-based control, autonomy, and simulation stacks for manipulators and multi-agent systems. He has driven end-to-end projects from novel MPC research and PyTorch-based state predictors to hardware validation on UR5e arms, and recently applied those skills in industry roles including Booz Allen and HITT Contracting. Comfortable in C++, Python, ROS, and real-time system integration, he focuses on robust, reactive behaviors that bridge cutting-edge research and practical deployment. Nathan’s background spans academic research on sparse success objectives and human-swarm interaction to production-oriented tooling and data pipelines, revealing a knack for turning complex control concepts into reliable fielded systems. Based in Virginia, he combines rigorous experimentation with pragmatic engineering to deliver autonomy that works outside the lab.
8 years of coding experience
4 years of employment as a software developer
Bachelor of Science - BS, Computer Engineering, Bachelor of Science - BS, Computer Engineering at University of North Carolina at Charlotte
Fulbright Summer Institute, Fulbright Summer Institute at University of Strathclyde
Master of Science - MS, Robotics, Master of Science - MS, Robotics at Oregon State University