Donald R. Reising serves as a Guerry and UC Foundation Professor of Electrical Engineering in the College of Engineering and Computer Science at the University of Tennessee at Chattanooga (UTC). He holds appointments in both the Electrical Engineering department and the Computational Science program, with active roles in university governance as Faculty Senate Chair (2022-2025) and member of multiple strategic committees including the PhD Computational Science Committee. B.S. in Electrical Engineering, University of Cincinnati (2006) M.S. in Electrical Engineering, Air Force Institute of Technology (2009) Ph.D. in Electrical Engineering, Air Force Institute of Technology (2012) Dr. Reising's research spans three interconnected domains: wireless security through Specific Emitter Identification (SEI) and RF fingerprinting, smart grid intelligence for real-time disturbance analysis, and radiation effects characterization in microelectronics. His work integrates machine learning with signal processing to solve critical infrastructure protection challenges, particularly in adversarial environments where traditional security measures fail. Recent publications demonstrate increasing focus on deep learning countermeasures against SEI spoofing attacks and edge-computing solutions for power grid resilience. His 15 most recent publications reveal strong emphasis on adversarial machine learning (6 articles), SEI robustness under environmental stressors (5 articles), and smart grid data analytics (3 articles), with growing interdisciplinary work in quantum correlations and transportation safety. This trajectory shows evolution from foundational RF fingerprinting techniques toward comprehensive security frameworks for critical infrastructure. IEEE Chattanooga Chapter's Outstanding Engineer Award (2022) UTC’s Outstanding University Service Award (2018) AFRL Sensors Directorate Dr. Samuel M. Burka Award (2013) Association of Old Crows Research Excellence Award (2009) MASINT Committee Academic Excellence Award (2009) Dr. Reising leads multiple research initiatives including the RF Security Lab and Smart Grid Analytics Group, securing consistent funding from DoD agencies (AFRL, ARL), NSF, and industry partners like EPRI. His service extends to advising graduate students through the Computational Science PhD program and directing undergraduate research in radiation effects characterization. Current projects focus on SEI resilience against deep learning attacks, quantum-enhanced signal processing, and edge-computing solutions for grid cybersecurity.
