Artificial Intelligence for Scalable and Sustainable Systems
In conjunction with the iSCSi – International Conference on Industry Sciences & Computer Sciences Innovation.
Workshop Chair
Professor Dr. Nuno Mateus-Coelho
Workshop Description
The AI-SSS Workshop 2024 aims to provide a dynamic platform to bring together academics, industry professionals, and researchers in the fields of artificial intelligence, scalable computing, and sustainability. We welcome original papers exploring knowledge about AI processes, scalability, and innovation in the realm of sustainable systems.
Accepted papers will be published and indexed by Scopus and Clarivate Conference Proceedings Citation Index – Web of Science (formerly ISI Thomson). In addition, extended versions of all accepted papers will be invited for potential inclusion in a book of chapters or a relevant AI or computing journal.
We invite submissions relating to (but not limited to) the following topics:
Workshop Topics and Areas of Interest
- Machine Learning in Scalable Systems: Deep dive into the application of various machine learning models and algorithms within large-scale and distributed systems. Explore performance optimization, efficiency, and scalability issues related to ML deployments.
- AI for Sustainability and Energy Efficiency: Explore how AI can be leveraged to optimize energy use, reduce carbon footprints, and drive sustainability in business processes and systems. Investigate the role of AI in predictive maintenance, energy forecasting, and other sustainability-focused applications.
- AI and High-Performance Computing: Analyze the synergies between AI and high-performance computing. Discuss the challenges and solutions in running AI applications on HPC systems, parallel computing strategies for AI, and advancements in hardware for AI.
- AI Security and Privacy in Scalable Systems: Investigate the unique security and privacy challenges brought about by the deployment of AI in scalable systems. Examine strategies for preserving data privacy, ensuring secure AI, and mitigating adversarial attacks.
- Explainable AI (XAI) in Scalable Environments: Delve into the significance and methods of making AI transparent and understandable in scalable environments. Discuss strategies and techniques for improving the interpretability and transparency of AI models, ensuring their reliability and trustworthiness.
- Distributed AI and Edge Computing: Study the increasing importance of edge computing in AI deployment, and its role in managing scalability. Explore the challenges and solutions in implementing AI in distributed systems, and the advancements in federated learning and decentralized AI.
- AI for Scalable Data Analytics: Discuss the role of AI and machine learning in dealing with the challenges of big data analytics. Explore techniques and solutions for improving the scalability of data processing and analytics workflows with AI.
- AI-driven Optimization in Scalable Systems: Explore how AI can help optimize processes, resource allocation, scheduling, and performance in scalable systems. Focus on the use of AI-driven models to make better decisions and improve efficiency.
New Deadline Dates
- New Deadline for paper submission: August 10, 2024
- New Notification of acceptance/rejection: August 25, 2024
- New Revised Version / Camera Ready: September 15, 2024
- Conference: October 29, 30, and 31, 2024
Previous Important Dates
- Deadline for paper submission: July 5, 2024
- Notification of acceptance/rejection: August 5, 2024
- Revised Version / Camera Ready: August 15, 2024
- Conference: October 29, 30, and 31, 2024
Submission Procedure
Please use the following link to submit your paper:
Paper format
Manuscripts must be written in English. Each manuscript should not exceed the maximum number of pages predefined for each submission type, considering the format available: