NOTE: New conference dates: May 16-17 On-line, May 24 in-person, Pittsburgh
The aim of CAIN’22 is to bring together researchers and practitioners in software engineering, in data-science and AI, and to build up a community that will target the new challenges emerging in Software Engineering for AI-enabled systems.
In development and implementation of AI-enabled systems, the main challenge is not to develop the best models/algorithms, but to provide support for the entire lifecycle – from a business idea, through collection, training, and management of data, code development, product deployment and operation, and its maintenance and evolution. There is a clear need for specific support of Software Engineering for AI.
CAIN has the following goals for the next few years.
- Identify the main challenges of AI engineering, from an AI and SE perspective, considering industrial needs and their current experiences;
- Create a roadmap capturing the research directions in AI engineering in relation to AI-based systems lifecycle;
- Contribute to a better understating of practical problems and understanding differences in approaches of data science and AI/ML and SE;
- Identify industrial challenges in building and using AI-enabled systems and contribute to solving them
- Build a thriving community of SE, and data-science and AI practitioners and researchers.
CAIN’22 will have all sessions in a single track. The following sessions are planned:
- Invited keynotes and panels
- Presentation of accepted papers
- Industrial Talks
- Poster presentations