The 25th International Conference on Algorithms and Architectures for Parallel Processing
Zhengzhou, Henan, China
October 30 - November 02, 2025
Important Dates
Paper Submission
July 15, 2025 (AoE time)
August 31, 2025 (AoE time)
Author Notification
September 15, 2025
Camera-Ready Submission
September 30, 2025
Registration Due
September 30, 2025
Conference Dates
October 30- November 02, 2025
Organizing Committee
Chairs
Xin Xie, Tianjin University, China
Yuan Yao, Northwestern Polytechnical University, China
Yu Li, Hangzhou Dianzi University, China
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IDC 2025 |
Download CFP: PDF
IDC: Workshop on Intelligent Distributed Computing Following the widespread adoption of distributed computing in fields like big data and cloud computing, researchers are advancing paradigms for intelligent distributed computing to meet new demands of AI-driven applications. To achieve enhanced computational efficiency and stringent data privacy, novel approaches (e.g., intelligent resource scheduling, federated learning, and privacy-preserving architectures) have emerged as foundations for next-generation systems. However, these approaches require adaptive optimization and secure multi-node coordination, thereby posing significant challenges for scalability and robustness in AI-integrated environments. To address such challenges, the integration of artificial intelligence techniques (e.g., multi-agent reinforcement learning, decentralized optimization, and AI-driven security mechanisms) offers transformative design pathways. Therefore, the synergy of AI and distributed computing is critical for enabling efficient, secure, and scalable intelligent computational platforms.We invite submissions from academia, government and industry that present novel research on the topics as following areas:
- Distributed Swarm Robotics Systems
- Distributed / Decentralized / Federated Machine Learning
- Intelligent Distributed Applications
- Intelligent Distributed and High-Performance Architecture
- Intelligent Distributed Knowledge Representation and Processing
- Intelligent Distributed Ledgers, Blockchains and AI
- Intelligent Energy Systems
- Intelligent Production Systems, Intelligent Transportation Systems
- Machine Learning Methods for Distributed Systems
- Multi-Agent Systems
- Multi-Agent Machine Learning
- Multi-Agent Reinforcement Learning
- Nature-Inspired Methods for Supervised and Unsupervised Data Mining
- Networked Intelligence, Organization and Management
- Parallel Metaheuristics for Optimization
- Smart City Applications, Smart Grid Applications
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