We are pleased to invite researchers, academics, and industry professionals to submit their latest work and proposals to the IEEE ICMLCN 2025.

This prestigious conference will be held in the vibrant city of Barcelona, Spain, from May 26 to 29, 2025.

Important Dates:

• Paper Submissions: 31 October 2024
• Special Session Proposals: 31 October 2024
• Demo Proposals: 13 December 2024
• Tutorial Proposals: 13 December 2024
• Industry Panel Proposals: 13 December 2024
• Acceptance Notification: 31 January 2025
• Camera-Ready: 14 February 2025

IEEE ICMLCN 2025 aims to unite leading experts in machine learning, communication, networking, and signal processing to discuss and promote cutting-edge innovations and applications.

It provides a dynamic platform for the exchange of ideas, fostering collaboration between academia and ;

For more information on call for papers and submission guidelines, please visit ;and 

The conference brings together researchers from the disciplines of Machine Learning (ML), Communication and Networking and Signal Processing, and aims at promoting fundamental and applied research of ML for designing and analyzing communication systems and networks, for developing communication protocols to support ML services, as well as for advancing distributed ML over communication networks.

The conference targets any communication and networking area, such as, but not limited to, wireless, satellite, optical, or molecular communications, Internet, and WLAN.

Topics of interest include: 

• ML and networking for intelligent transportation systems
• ML and networking for smart grids
• ML for signal processing in communication and networking 
• ML for the MAC layer
• ML for the physical layer
• ML for the transport layer
• Communication-efficient distributed ML
• Distributed ML over communication networks
• Federated learning and communications
• Learn to transmit and receive
• Resource management and network optimization
• Semantic communications and ML
• Wireless communication to support ML services
• Wireless networking to support ML services • ML and IoT
• Large language models (LLMs) for communication and networking
• ML and molecular networks
• ML and optical networks
• ML in Intelligent reflecting surfaces
• ML and networking in smart cities
• Decentralized transmission optimization for edge learning
• Distributed multi-agent reinforcement learning
• Edge learning in wireless networks
• Experiments and testbeds
• Integrated distributed optimization with edge learning
• Integrated sensing and communication via ML
• Network architectures and protocols for edge learning
• Over-the-air computation for edge learning
• Privacy and security issues with ML over networks
• Trustworthiness in ML decisions