Biography
Abir Ray is a seasoned technology leader and academic, serving as CEO/CTO of Expression Networks LLC and a Visiting Assistant Professor of Practice at Cornell University. With over 20 years of experience in technology and defense, he has specialized in electromagnetic spectrum (EMS) operations, secure communications, and advanced signal processing. His work integrates artificial intelligence, machine learning, and modular architectures to optimize spectrum management and counter interference in complex, multi-domain environments. As an active board member of the National Spectrum Consortium and a committee member with the FCC, Abir plays a critical role in shaping policy and driving innovation in EMS technologies.
Research Interests
My research focuses on the development and application of advanced technologies in EMS operations. I explore areas such as spectrum management, signal processing, and the use of AI/ML to enhance secure communications and operational resilience. Additionally, I investigate digital twin technologies and model-based systems engineering (MBSE) as transformative tools for optimizing the design, testing, and operational processes across various industries, including defense, aerospace, and smart cities.
Teaching Interests
At Cornell, I teach graduate-level courses on Digital Twins and Model-Based Systems Engineering, where I emphasize the integration of theoretical knowledge with practical applications. I am passionate about equipping students with the skills to create and leverage digital representations of physical systems, fostering innovative problem-solving and critical thinking in modern engineering contexts. My teaching approach bridges academic rigor with real-world challenges, preparing students to contribute effectively to technological advancements in their respective fields.
Selected Publications
Selected publications include peer-reviewed articles and conference papers on spectrum management, digital twin technologies, and model-based systems engineering. (A comprehensive list is available upon request.)
Yu, L., & Ray, A. (2024). An LLM Maturity Model for Reliable and Transparent Text-to-Query. arXiv preprint arXiv:2402.14855v1. https://doi.org/10.48550/arXiv.2402.14855
Ray, A. (2024). CareCERT: Increasing Cybersecurity Resilience for Healthcare Systems (Doctoral dissertation, The George Washington University).
Ray, A. (2023). Machine learning based spectrum fingerprinting of drones for defensive cyber operations (Master’s thesis, Harvard University Division of Continuing Education).
Education
Doctor of Philosophy in Industrial and Systems Engineering – University of Tennessee, Knoxville, TN (Expected Spring 2026)
Doctor of Engineering in Cybersecurity Analytics – George Washington University, Washington, DC
Master of Liberal Arts in Software Engineering – Harvard University, Cambridge, MA
Master of Engineering in Systems Engineering – Cornell University, Ithaca, NY
Bachelor of Arts in Interdisciplinary Studies – University of Virginia, Charlottesville, VA