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Principal Artificial Intelligence Engineer at MITRE
I specialize in data science for cybersecurity, working at the intersection of AI/ML, big data, and defensive cyber operations. My career began in MITRE’s Natural Language Processing department, where I built a strong foundation in AI techniques that I applied to cybersecurity applications. As a founding member of MITRE’s Data Science department, I helped shape its approach to distributed machine learning algorithm development and large-scale cybersecurity analytics. My technical work spans malware forensics, biometric authentication, petabyte-scale ML-based threat detection, and graph visualization for cyber threat hunting. My Ph.D. research on Android OS security gave me experience navigating highly complex, multi-layered software systems, from the application layer down to the kernel, which honed my software development, problem solving, and critical thinking skills. Currently, I help government organizations develop their Cyber-AI strategies and lead a large team of engineers prototyping generative AI solutions for defensive cyber operations, with a focus on retrieval-augmented generation (RAG) systems and MLops-driven evaluation for rapid, technically rigorous, repeatable experimentation at scale. I also serve as a Group Leader for a team of data scientists ranging from entry to late career-level, removing barriers and helping them grow at different career stages while aligning their work with unique and impactful challenges. I’m driven by the challenge of applying AI to real-world cyber threats—building scalable, high-impact solutions while mentoring the next generation of data scientists and AI engineers.
University of Massachusetts Lowell
Doctor of Philosophy (PhD), Computer Science
January 1, 2013 – January 1, 2018
University of Massachusetts Lowell
BS, Computer Science
January 1, 2006 – January 1, 2010
MITRE
Principal Cyber Data Scientist
January 1, 2009 – Present
Bedford, Massachusetts, United States
Cultural Fit Analysis
The candidate's experience is primarily within a single organization (MITRE) and focused on 'Cyber Data Scientist' roles. While AI/MLOps skills are relevant, the breadth of project diversity and exposure to different industry cultures is not evident from the provided data. This may indicate a more specialized background rather than broad industry exposure, potentially impacting cultural fit in a diverse commercial environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The psychometric test score is 0, providing no insights.