Abstract
Artificial Intelligence (AI) is rapidly reshaping the landscape of scientific discovery by enabling the development of novel models that tackle complex, data- and computation-intensive problems. Scientific challenges, in turn, provide rich, use-inspired settings that push the boundaries of AI research. This virtuous cycle is increasingly driven by cross-disciplinary collaboration, where advances in AI and domain sciences co-evolve to accelerate innovation. In this plenary panel, we will examine the opportunities and challenges in designing cutting-edge AI models for scientific discovery, and high- light the transformative potential of cross-disciplinary partnerships in shaping the future of both AI and science.
| Original language | English (US) |
|---|---|
| Title of host publication | KDD 2025 - Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining |
| Publisher | Association for Computing Machinery |
| Pages | 5988 |
| Number of pages | 1 |
| ISBN (Electronic) | 9798400714542 |
| DOIs | |
| State | Published - Aug 3 2025 |
| Event | 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025 - Toronto, Canada Duration: Aug 3 2025 → Aug 7 2025 |
Publication series
| Name | Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining |
|---|---|
| Volume | 2 |
| ISSN (Print) | 2154-817X |
Conference
| Conference | 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2025 |
|---|---|
| Country/Territory | Canada |
| City | Toronto |
| Period | 8/3/25 → 8/7/25 |
Bibliographical note
Publisher Copyright:© 2025 Owner/Author.
Keywords
- ai for science
- artificial intelligence
- machine learning
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