Call for Papers: Advancing the Frontiers of Engineering and Optimisation for AI Systems at Scale

AISystems​ is an international scholarly journal aiming to be a central hub for knowledge exchange in the field of AI systems engineering and optimisation at scale. As AI models grow increasingly complex and integral across industries, the challenges in their system design, deployment, maintenance, and governance have become critical. This journal addresses this need by focusing on bridging the gap between cutting-edge model research and the industrial deployment of reliable systems.

The journal scope includes, but is not limited to:

• AI System Engineering: Including architecture design, deployment strategies, and performance optimisation.

• Large-scale & Multimodal Systems: Development, evaluation, and application.

• System Robustness: Testing, benchmarking, validation, and failure analysis.

• MLOps & Lifecycle Management: CI/CD, model governance.

• Trustworthy AI: Transparency, fairness, accountability, and bias mitigation.

• Edge AI & Distributed Inference: Embedded intelligence and distributed frameworks.

• Autonomous Agents & Automation: Multi-agent systems and automated pipelines.

• Hardware Acceleration & Green Computing: GPU/TPU optimisation, energy-efficient AI, and compute infrastructure.

Target Audience & Contributors:​ We welcome submissions from academics, researchers in industrial labs, as well as frontline AI system engineers, architects, and product leads. Your contributions will help steer the field of AI systems towards greater efficiency, reliability, and sustainability.

Submit your research and help define the future of AI systems with us.

For submission guidelines and further information, please visit the journal's official website.