The International Conference on Intelligent Computing and Systems at the Edge (ICEdge) 2025 will be held December 18th-20th, 2025 at the Indian Institute of Science in Bangalore, India.
This effort is a collaboration between many universities and industry partners worldwide, with Nelms Institute faculty Dr. Swarup Bhunia as a General Chair, Dr. Baibhab Chatterjee as a Program Chair, and Dr. Mingyue Ji as a Special Session Chair.
More information can be found at the conference website.
About ICEdge
The tremendous progress in Artificial Intelligence (AI) and Internet of Things (IoT) technologies has opened up fresh possibilities for innovation and enhanced system-level efficiency across diverse vertical spaces in the technologies involved. The confluence of intelligence, pervasiveness, and energy efficiency, fueled by artificial intelligence of things (AIoT), is paving the way for a new era of intelligent systems capable of real-time sensing, processing, energy-efficient secure communication and actuation, eventually resulting in improved system-level decision-making and resource optimization at the Edge. This conference on Intelligent Computing and Systems at the Edge seeks to unite researchers, practitioners, and industry experts to exchange their most recent discoveries, experiences, and insights in the exciting domain of AIoT and System Development at the Edge.
Topics
We solicit high-quality submissions from you. All accepted papers will be published in IEEE Xplore, and the top selected papers will be invited for a Journal Version in IEEE Design and Test.
The Full list of tracks is available at: https://icedge.org/full-list-of-tracks/
The general topics of interest for the conference include, but are not limited to:
- Computing Architectures and Technologies at the Edge
- Tiny Machine Learning for the Edge
- Generative AI for Edge IoT
- AI and IoT for the Metaverse
- Energy-efficient and Secure Communication Techniques for AIoT Systems
- Emerging AI algorithms and architectures for IoT systems
- Machine learning and deep learning for IoT systems
- AI-driven IoT security and privacy concerns and solutions
- AI-based Industrial IoT data analytics/visualization
- IoT-enabled AI applications, involving smart cities, smart homes, smart cars, etc.
- Natural language processing and conversational AI for the Edge
- AIoT applications in robotics and industrial automation
- Scalability, performance, and energy efficiency in AIoT systems at the Edge
- Intelligent Battery and Power Management for AIoT systems
- Ethical considerations and need for Standards in AIoT Systems