Team

Paul K. Mandal is an applied AI researcher and engineer focused on building secure, high-performance machine learning systems for healthcare and defense. At Neurint, Paul leads the design and implementation of federated learning frameworks, medical and mission-focused computer vision systems, and edge-deployable models that operate in real-world environments rather than curated benchmarks.

Paul’s background combines hands-on research, systems engineering, and operational experience. He has led AI/ML efforts on Department of Defense programs, including work on distributed targeting and sensor-to-shooter pipelines, and has published peer-reviewed research in federated learning and clinical AI. His technical expertise spans deep learning, distributed systems, embedded and FPGA-based acceleration, and cybersecurity-aware AI system design.

Paul holds degrees in computer engineering, applied mathematics, and cybersecurity, and is pursuing further graduate work in computer science. He has served as an Army officer in Infantry, Signal, and Cyber roles, and brings that operational perspective into Neurint’s work with both healthcare and defense partners.

• Founder & Principal AI Engineer at Neurint
• Research focus: federated learning, clinical AI, and secure ML systems
• Experience across defense, healthcare, and dual-use AI applications
• Background in Infantry, Signal, and Cyber operations