CAIN 2027

Welcome to CAIN 2027 — 6th International Conference on AI Engineering – Software Engineering for AI

CAIN’27 is co-located with the 49th International Conference on Software Engineering (ICSE’27). Please find more information about ICSE’27 here.

CAIN is the premier venue for research on AI Engineering (or Software Engineering for AI-Enabled Systems) – the application of software engineering principles to building software with one or more AI/ML components. The CAIN conference series aims to bring together researchers and practitioners in software engineering, data science, and AI as part of a growing community focused on addressing not just training models to beat benchmarks, but also on developing software applications that provide value to users and society. In the development and implementation of AI-enabled systems, experience has shown that the main challenge is not to develop the best models or algorithms but rather to provide support for the entire system life cycle – from a business idea, through data collection, model training, system design and development around the model(s), product deployment and operation, and finally system maintenance and evolution. Therefore, there is a clear need to advance the field of AI Engineering. While there are many well-established venues in AI and machine learning (ML), CAIN is unique in taking a system- and life-cycle-oriented perspective on AI engineering.

CAIN has the following goals:

• Identify and clearly describe the main challenges in AI Engineering based on industrial needs and experiences, and contribute to solving them.
• Foster high-quality publications and discussions leading to research directions for AI engineering, the life cycle of AI-enabled systems, and the software engineering practices to support it.
• Contribute to a better understanding of the differences between data science and software engineering approaches, such that practices from both fields can come together to solve practical problems in AI engineering.
• Build a thriving community of software engineering, data science, and AI practitioners and researchers, who want to improve how we engineer AI-enabled systems.

CAIN 2027 will have sessions that combine submissions from multiple tracks:

• Invited keynotes and panels
• Presentations of accepted research and experience papers
• Industry talks
• Journal-first presentations
• Poster presentations
• Doctoral symposium presentations