Eric Yocam, PhD, DBA

(Lecturer)

Dr. Yocam’s research program is characterized by a deep integration of quantum algorithms and secure communication protocols. His work in the quantum domain includes the development of hybrid quantum-classical path optimization models for methane detection, which leverage remote quantum intensity prediction. He has pioneered dynamic quantum-resistant selective encryption approaches tailored for resource-constrained agricultural sensors and multi-level post-quantum encryption techniques for images utilizing the Quantum Fourier Transform. Furthermore, his research explores the benchmarking and performance assessment of predictive models across classical, quantum-inspired, and quantum frameworks, as well as the implementation of event-driven leak prediction via quantum spiking neural networks. These contributions, alongside his extensive work in 5G mobile network security and machine learning-based identification of malicious activity, establish his broader commitment to hardening complex systems against emerging computational threats.