Workshop on Cross-Disciplinary Challenges and Opportunities in AI Applications to Science and Engineering (C2OA2SE)

Author(s):

Sarah Kitchen and Steven Thurman

Abstract:

This report is a summary of the work presented at the Workshop on Cross-Disciplinary Challenges and Opportunities in AI Applications to Science and Engineering (C2OA2SE), which was held to address the integration of AI into diverse scientific and engineering fields. Driven by recent advances in AI algorithms, data availability, and computational resources, the workshop convened 13 invited speakers and 21 additional participants to examine state-of-the-art AI approaches and identify common challenges across disciplines. The workshop objectives centered on fostering cross-disciplinary dialogue, sharing complex problems, and characterizing approaches for rigorous investigation of complex systems leveraging AI. Activities included technical talks, focused breakout sessions, and large group discussions designed to facilitate the exchange of knowledge and best practices. Organized by the Michigan Tech Research Institute and ARL, C2OA2SE highlighted the need for a cross-disciplinary view of AI research to maximize benefits and mitigate risks during integration into STEM disciplines. This report details the workshop’s organization, format, participant demographics, outcomes, and conclusions, laying the groundwork for future collaborative efforts in this rapidly evolving field.