In recent years, foundational research in data science, artificial intelligence (AI) and machine learn- ing (ML) have drawn incredible interest in application to a wide range of data driven approaches to scientific and engineering discovery. These techniques can be used to review and mine scientific literature, generate new hypotheses, design experiments, and make accurate predictions. Moreover, AI is ushering in a new scientific revolution by making remarkable achievements in a number of fields. Workshops and meetings were held by the U.S. National Science Foundation (NSF) and other organizations to discuss cutting-edge breakthroughs and emerging trends as well as to disclose fresh opportunities and new understanding for advancing scientific frontier. However, the majority of events are structured for a particular scientific field in silos. A paradigm-shifting scientific revolution might be made possible by integrating important discoveries from these incidents and developing fresh, cogent insights.
The goal of the meta-workshop is to provide NSF with information on the state of complementary research in data analytics, AI, machine learning as well as domain sciences. The subjects of interest include identifying specific subject areas with high potential for data-driven approaches to discovery, appropriate community size and AI methods widely incorporated to assist the development, promising examples that benefit from supporting methods with broad applicability across domains, and the best practices to cross boundaries from diverse scientific disciplines. Finally, syn- ergies between the theme (data, AI/ML) and the other themes (Digital Twins, Smart Sensors and Analytics, Rigorous and Reproducible Scientific Reasoning, and Programmable and Self Driving Labs) will be explored.
Zoom Link: https://virginia.zoom.us/j/98799084466?pwd=QWVqb0E0dnNEOTBYQ1dnN3NpbVErdz09
Notes: https://drive.google.com/drive/folders/1mRRUCAjOcLS_APrlPsQ-0nLbRJO-xRsx
Recordings (private): https://drive.google.com/drive/folders/1JCyIq32DNXwr-1eYn5tNLqJG2Xe9fUfd
Breakout assignment: https://docs.google.com/spreadsheets/d/1fO-YYPaiQD0RNpb4N4An23YwO4Tnwf2B_NgH9Mad9XA/edit?usp=sharing
Breakout coordination guideline: https://docs.google.com/presentation/d/1WQNskZku2DqdpznMptcguQ37qaylNJv0aQ2D7pxzbJk/edit?usp=sharing
Instructions to upload slide: https://docs.google.com/presentation/d/1Uh-8w2iaJmdgRNtJ14aVfMgZ7gAdgEuakGvEps0QMBs/edit?usp=sharing
Slack: https://nsf-ai2ased.slack.com (join the workspace here)
Registration: https://indico.cern.ch/event/1325897/registrations/
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| NSF Award 2337647 |
