William Curran is an AI and autonomy leader with 12 years of experience specializing in resilient autonomy for long-duration, safety-critical systems across space, maritime, and terrestrial domains. He combines deep research credentials (PhD in Robotics) with hands-on program leadership, having led multi-million dollar DoD and NASA projects that applied reinforcement learning, fault management, and physics-based modeling to certify and sustain autonomous behaviors. At MITRE and prior roles he has translated novel techniques—platform introspection, introspective decision making, and multi-fidelity simulation—into practical solutions for rovers, underwater vehicles, and minimally manned surface vessels. He has a track record of bridging theory and practice, from developing dimensionality-reduced RL for high-dimensional robot control to hybrid control/DRL for compact hydraulic robots. Based in Virginia, he enjoys tackling the hard systems problems that enable long deployments with minimal human oversight and mentoring teams to do the same. Notably, his work includes adversarial RL for active fault detection in space habitats, an uncommon but impactful application of learning to safety-critical certification.
12 years of coding experience
14 years of employment as a software developer
Bachelor's Degree, Computer Science, Cum Laude, Bachelor's Degree, Computer Science, Cum Laude at Oregon State University
Code for automating a PERMOBIL wheelchair for the ALS foundation.
Contributions:46 commits, 2 PRs, 11 pushes in 3 years 10 months
alspythonwheelchairfoundation
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