معرفی
Philippe Ciblat is a Professor at TELECOM Paris Tech, affiliated with the Department of Signal Processing and Communications. His research spans signal processing, wireless communications, and machine learning applications in networking. He has collaborated extensively with institutions like the University of Paris-Saclay and international researchers in areas such as cooperative communication protocols, resource allocation, and coding theory.
- Research Interests: Machine learning for signal processing, wireless channel modeling (Rician fading), lattice decoding, caching strategies, and distributed optimization.
- Notable Work: Pioneered transformer-based packet scheduling, neural network approaches to lattice decoding, and effective capacity analysis in fading channels.
His contributions include over 170 publications in top venues (IEEE Trans. Signal Process., IEEE Trans. Wireless Commun.) and collaborations with industry partners on practical implementations like cache-aided polar coding. He has advised multiple researchers in distributed systems and wireless resource management.
