IEEE Journal of Selected Topics in Signal Processing (JSTSP) Special Issue on “Autonomous and Evolutive Optimization in Networked AI“.

Special Issue Overview:
This Special Issue addresses autonomous and evolutive optimization in networked AI, a transformative paradigm that integrates traditional adaptive signal processing with modern deep learning approaches. It explores online, self-evolving mechanisms that enable distributed models to improve through dynamic data acquisition, reward generation, and pseudo-labeling. Emphasis is placed on unifying supervised and reinforcement learning within multi-agent, time-varying environments. The issue highlights scalable, self-optimizing AI architectures applicable to communications, IoT, and intelligent signal processing. Its goal is to advance foundational methodologies and promote impactful real-world applications in next-generation AI systems.

Topics of Interest Include:
• Foundations and principles of signal processing in networking systems of AI
• Mathematical underpinnings of networked AI optimization
• End-cloud collaborative large language models with evolutive optimization
• Coordinated sensing and control processing in autonomous multi-agent AI systems
• Multimodal and adaptive signal processing with networked AI
• Networked AI for cognitive communications and networks
• Online model-drift detection and compensation mechanisms
• Networked AI enhanced signal processing in non-stationary environments
• Practices of autonomous and evolutive learning for networked AI systems

Key Dates:
• Submission Deadline: June 15, 2026
• First Review Due: August 14, 2026
• Final Decision: November 20, 2026
• Publication: January 2027

Links:
IEEE JSTSP Special Issue Call: https://signalprocessingsociety.org/events/ieee-jstsp-special-issue-autonomous-and-evolutive-optimization-networked-ai
Guidelines: https://signalprocessingsociety.org/publications-resources/ieee-journal-selected-topics-signal-processing
Submission: https://mc.manuscriptcentral.com/sps-ieee

Guest Editors:
Liang Song, Fudan University, China, songl@fudan.edu.cn (Lead GE)
Jiangchuan Liu, Simon Fraser University, Canada, jcliu@sfu.ca
Amit Dvir, Ariel University, Israel, amitdv@g.ariel.ac.il
Athanassios Skodras, University of Patras, Greece, skodras@upatras.gr
Victor C.M. Leung, University of British Columbia, Canada, vleung@ece.ubc.ca
Qi Bi, China Telecom Research Institute, China, qibi@chinatelecom.cn