Joshua Kraunelis

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.