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
Hanning Zhang, China Unicom, China
Yu Weng, Minzu University of China, China
Xueyun Zeng, Beijing University of Post and Telecommunications, China
Shiguo Lian, China Unicom, China
Ti Wang, China Unicom, China
Ruitao Ma, China Unicom, China
Jianwei Fang, China Unicom, China
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SAID-Eco 2025 |
Download CFP: PDF
SAID-Eco: ICA3PP Workshop on Symbiotic AI and Data Ecosystems: The rapid evolution of AI and data science has revealed a critical interdependence: AI systems rely on high-quality data for training, while data ecosystems leverage AI for curation, enrichment, and value extraction. Modern AI systems demand unprecedented volumes of high-quality, diverse, and dynamic data to achieve robustness, while data ecosystems increasingly rely on AI for autonomous curation, enrichment, and value extraction. This bidirectional symbiosis where AI algorithms optimize data infrastructures and data fuels AI’s adaptive intelligence promises to redefine the future of intelligent systems. Yet, this bidirectional relationship introduces unprecedented risks adversarial data poisoning, model inversion attacks, and autonomous bias propagation that threaten the sustainability of AI-data ecosystems. The Workshop on Symbiotic AI and Data Ecosystems (SAID-Eco) addresses the bidirectional synergy between AI and data, focusing on systems, algorithms, security and applications where each domain fuels the other’s advancement. SAID-Eco unites AI researchers, data engineers, practitioners, and industry practitioners to discuss the latest innovations, challenges, and future directions in AI-driven data generation, data-centric AI optimization, integrating AI safety & trustworthy data, and real-world applications.We invite submissions from academia, government and industry that present novel research on the topics as following areas:
- Data-driven AI evolution: Techniques for continuously improving AI models using real-time data feedback loops.
- AI-enhanced data curation: Methods for using AI to discovery, augmentation, clean, annotate, and enrich datasets.
- Generative AI for synthetic data generation and privacy.
- Real-world applications (Healthcare, Smart Cities, IoT and Edge Computing, Industrial Automation).
- AI-data systems, Data Service Design, Data Assets, and AI in management, accounting, governance.
- AI and Data Security & Trustworthiness.
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