Research Director (AI & Autonomy) + AI Technical Fellow
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MITRE's Technical Fellow for Artificial Intelligence. I lead our independent research program in AI & autonomy, setting strategy and driving impact on high stakes problems by leading AI innovation thats cut across our Federal AI Sandbox, six Federally Funded Research & Development Centers, and 7000+ staff. Distinguished AI scientist with 25 years of specialization in neural networks, language processing and GenAI, and applied AI pathfinding.
Massachusetts Institute of Technology
AI / Robotics
January 1, 2004 – January 1, 2006
Carnegie Mellon University
BS, Computer Science, Cognitive Science
January 1, 1997 – January 1, 2001
Institute of Neuromorphic Engineering
Director
October 1, 2017 – Present
Telluride, Colorado
MITRE Corporation
Research Director (AI & Autonomy) + AI Technical Fellow
August 1, 2001 – Present
Cultural Fit Analysis
The candidate's background is heavily focused on AI, robotics, and neuromorphic engineering, with significant experience in federal and research environments. While their technical depth in AI is exceptional, their resume does not explicitly detail experience with traditional 'Big Data' technologies (e.g., Hadoop, Spark, Kafka, data warehousing, ETL pipelines) which are core to a Big Data Engineer role. This suggests a potential mismatch with the specific technical requirements and cultural expectations of a typical Big Data engineering team, which often involves large-scale data processing infrastructure rather than pure AI model development and research. The lack of project diversity in traditional data engineering domains indicates a potential gap in cultural fit for a dedicated Big Data Engineer role.
Soft Skills & Operational Fit
The candidate's extensive leadership experience in AI research and development, coupled with their role in fostering an AI-native workforce, suggests strong leadership, strategic thinking, and collaboration skills. Their involvement in the Telluride Neuromorphic Cognition Engineering Workshop series indicates a commitment to collaborative development and knowledge sharing. However, specific data on stress handling, work attitude, or direct team collaboration from psychometric tests is not available.