Calling all electrical and electronics engineers: The Institute of Electrical and Electronics Engineers Journal of Selected Topics in Signal Processing (IEEE JSTSP) is seeking manuscripts for its special issue on Autonomous and Evolutive Optimization in Networked AI, slated for publication in January 2027.
Autonomous and evolutive optimization in networked AI integrates traditional knowledge based signal processing techniques and data-centric deep neural network models to continually acquire high quality data in the continuous inference of AI models, not only mimicking how human organizations evolve and learn beyond induvial machine learning paradigms, but can unify supervised and reinforced learning in the networking systems of AI via adaptive signal processing.
By leveraging dynamic interactions among multi-agent systems, it enables autonomous self-optimization and evolution of networked AI, ensuring robust performance in time-varying environments without human interventions, and with much scalable complexity. The interdisciplinary nature of adaptive networked AI not only influences Signal Processing, Internet of Things, Communication, and Computer Societies, but promotes applications such as industry-specific large language models, scene-adaptive auto-driving systems, and real-time 3D reconstruction.
Submission deadline is June 15, 2026, with first review completed by Aug. 14, 2026, revised manuscripts due by Oct. 1, 2026, second review Nov. 2, 2026, and final decisions on manuscripts by Nov. 20, 2026. Publication is slated for January 2027.
Topics IEEE JSTPS is seeking for this special issue include the following:
• 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 in networked AI
• Networked AI enhanced signal processing systems in non-stationary environments
• Practices of autonomous and evolutive learning for networked AI systems
For more information on submission requirements and instructions go here. To submit a manuscript go here.
