Summary
James Ecker is an AI and ML research lead at NASA Langley with over 18 years of software engineering experience and a decade of focused work in machine learning and autonomous systems. He designs and leads projects in generative AI, deep learning, and deep reinforcement learning for space robotics, on-orbit servicing, and urban air mobility, including cloud-native distributed task-allocation services for multi-agent fleets. His work spans NLP-driven knowledge representation and cognitive systems to policy optimization for autonomous flight, often leveraging HPC, GPU-accelerated frameworks, and synthetic-data generative models to address sparse aerospace datasets. Comfortable in Python, C/C++, Java, and functional languages like Scheme and Clojure, he couples rigorous research with production-focused engineering to move novel algorithms toward operational use. Based in Hampton, Virginia, he brings a rare combination of deep academic grounding (Georgia Tech) and hands-on systems development from national labs to NASA missions.
10 years of coding experience
7 years of employment as a software developer
Master’s Degree Computer Science, Master’s Degree Computer Science at Georgia Institute of Technology
Bachelor’s Degree Computer Science, Bachelor’s Degree Computer Science at Florida Southern College
Kathleen Senior High School