Distributed Machine Learning over Wireless Networks: From Classical to Quantum Approaches

#machine#Learning#Quantum#Wireless#network

FAMU-FSU College of Engineering & IEEE Tallahassee Section, PES Chapter, LMAG Joint Technical Seminar

Title: Distributed Machine Learning over Wireless Networks: From Classical to Quantum Approaches

Speaker: Dr. Dinh C. Nguyen, Department of Electrical and Computer Engineering, University of Alabama in Huntsville

Date: Friday, December 5, 2025, 14:00 – 15:15

Location: CAPS Seminar Room 120 (2000 Levy Avenue, Building A, Tallahassee, FL 32310)

Abstract

The emergence of distributed machine learning has transformed how intelligent systems are designed and deployed across wireless networks. This talk will explore the progression of Federated Learning (FL) and its quantum counterpart toward developing scalable, secure, and efficient distributed intelligence in wireless systems. The talk will consist of two main parts. The first part focuses on FL over wireless networks, emphasizing key design aspects such as communication resource allocation and security mechanisms to ensure reliable machine learning model training under realistic network constraints. The second part expands the discussion to Quantum Federated Learning (QFL), addressing the challenges posed by limited qubit counts in near-term quantum devices through innovative qubit reuse strategies and enhanced model explainability to improve transparency and trust in quantum-driven learning systems. Real-world applications of FL and QFL will be showcased in Internet of Things (IoT) applications including smart grid. Finally, we will outline open challenges and promising research directions toward achieving trustworthy, high-performance, and quantum-driven distributed learning over wireless networks.

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• 2000 Levy Ave
• Tallahassee, Florida
• United States 32310
• Building: BLDG. A
• Room Number: 120

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