Devu M Shila

Background

About Devu M Shila

I am the Founder and CEO of Unknot.id, a pioneering AI startup reimagining spatial intelligence for both humans and assets—without relying on GPS or added infrastructure. Unknot.id was born from a deep commitment to the belief that meaningful, privacy-conscious intelligence can be extracted from everyday sensors—and that spatial awareness, when done right, can transform how people and machines move through the world. Our universal location platform extracts high-fidelity insights from noisy COTS sensor data—blending movement, context, and identity—to power applications ranging from operational awareness and emergency response to fraud detection and indoor navigation. Before founding Unknot.id, I led Research and Innovation at United Technologies (now Raytheon Technologies), where I focused on advancing frictionless security and privacy through applied AI. In roles spanning Principal Investigator, Cybersecurity Advisor, and Strategic Technologist, I helped shape technical roadmaps, advised C-suite leadership, and led national security initiatives across government and industry. As co-founder of the Security and Privacy group, I directed multi-million-dollar programs funded by DARPA, DOE, DHS, and NSF—efforts rooted in interdisciplinary collaboration and long-term impact. Throughout, I remained committed to mentoring emerging talent and fostering innovation at the edge of AI and cyber-physical systems. That work led to breakthroughs across domains. Collaborations with Harvard Medical School, Brigham and Women’s Hospital, and the University of Rochester developed an advanced mobile-based digital phenotyping for early detection of TBIs and neurodegenerative conditions under DARPA sponsorship. At DHS S&T, I contributed to the development of a mobile access system that used human behavioral signals instead of passwords. With the Department of Energy and UIUC, I helped shape self-healing distributed energy infrastructures that respond to anomalies in real time. Work with IBM improved mobile malware detection by fusing static, dynamic, and metadata signals. A collaboration with Johns Hopkins, supported by NSF, explored audio-sensor-based alternatives to CAPTCHA to counter deepfakes and bots. I hold a PhD with the highest academic achievement award and an MS in Computer Engineering, with specializations in AI, cybersecurity, and statistics. My work has been recognized through national research fellowships, technical excellence awards, Women of Innovation honors, and outstanding achievement accolades.