GenAINet: Generative AI for Next-Generation Networking and Communications

Important Dates:

• July 24, 2025: Abstract Submission Deadline
• July 31, 2025: Paper Submission Deadline
• December 8, 2025: Acceptance Notification

For more details about INFOCOM 2026 and GenAINet, please visit the official website at https://infocom2026.ieee-infocom.org/.

General Co-Chairs:

• Tomoaki Ohtsuki (Keio University, Japan).
• Zhu Han (University of Houston, USA).
• Octavia Dobre (Memorial University, Canada).

Scope and Topics of the Workshop:

The rise of large-scale generative models, such as diffusion models, GANs, and LLMs, has transformed the field of machine learning and opened new avenues in networking. While traditional AI has largely focused on classification and prediction, generative AI (GenAI) presents opportunities for innovation in areas like automated network architecture, synthetic data generation, and adaptive network optimization.

As intelligent devices increasingly generate data locally, we must rethink the role of communication networks, shifting from mere data transport to active information generation.

GenAINet 2026 will serve as a platform for discussing early-stage research and experimental results at the intersection of generative AI and networking. The workshop will explore how advancements in generative models can address challenges in network design, operations, and security, and how networks must evolve to support GenAI services.

Key Topics Include:

• GenAI-Native Network Architectures and Protocols
• Resource Management and Quality of Experience (QoE) for GenAI Services
• Distributed and Federated GenAI over Networks
• Security, Privacy, and Trust in GenAI Networks
• GenAI-Driven Network Operations and Applications

Tags

• Techinical Co-sponsored event
• INFOCOM 2026 Workshop - GenAINet