Chairs

Introduction

With the rapid emergence of large AI models and the growing deployment of IoT applications, edge computing is driven towards perceptive and adaptive intelligence. The next-generation edge systems should meet the low-latency, high-bandwidth, and high-reliability demands while possessing the capability of perceiving environmental changes. This track focuses on Perceptive Edge Intelligence with Adaptive Learning and Resource Optimization, emphasizing how adaptive learning, collaborative intelligence, and resource-aware optimization enable edge systems to perceive environmental changes and make adaptive adjustments. We aim to gather cutting-edge theoretical advances, algorithmic innovations, and practical systems for adaptive model optimization and federated collaboration for intelligent resource management.

Topics

• Perceptive Adaptive Learning for Edge Intelligence
• Federated and Personalized Learning in Dynamic Edge Environments
• Context-Aware Service Caching and Edge-Cloud Offloading
• Collaborative Resource Optimization in Perceptive Edge-Cloud Systems
• Resource-Aware Model Optimization and Adaptation for Edge Services

Important Date

We are pleased to announce the important dates for PDCAT 2026. Please mark your calendars!
All deadlines are based on Anywhere on Earth (AoE), at midnight on the specified date.

• Paper Submission Deadline: 31 August, 2026 (AoE)
• Notification of Acceptance: 10 October, 2026
• Camera-Ready Submission Deadline: 31 October, 2026
• Conference Dates: 4-6 December, 2026