Dr. Kejie Lu is a Professor at the University of Puerto Rico–Mayaguez, where he conducts research at the intersection of edge computing, wireless communications, and aerospace systems engineering. His recent work focuses on workload prediction in computing power networks, differential privacy mechanisms for deep learning, and the security of federated learning. He has made significant contributions to unmanned aerial vehicle (UAV) communications, including the design of on-demand emergency aerial networks using directional antennas and the development of SDR-based LTE base stations for airborne platforms. His research also addresses safety in autonomous driving through age-of-information-optimized task scheduling and efficient verification schemes for coded edge computing. His work has appeared in leading venues such as IEEE Transactions on Cloud Computing, IEEE Internet of Things Journal, and IEEE Transactions on Vehicular Technology.
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