Machine Learning for Science!
During this panel with FRIB scientists, we will explore how they are using machine learning and artificial intelligence to propel their research and tasks. The scientists will briefly introduce themselves and their work before we switch our focus to broad discussion. We expect to explore a wide range of topics including machine learning applications to practice and pedagogy, the discovery of more efficient and descriptive numerical models, the acquisition of business intelligence for future research funding, and monitoring our faculty's contributions to the Sustainable Development Goals.
Presented by:
- Pablo Giuliani, Research Associate, Facility for Rare Isotope Beams, Michigan State University
- Kyle Godbey, Research Assistant Professor, Facility for Rare Isotope Beams, Michigan State University
- Charla Burnett, International Data Scientist, International Studies and Programs, Michigan State University
- Aaron Phillip, Undergraduate Student, Facility for Rare Isotopes Beams, Michigan State University
- Wolfgang Banzhaf, Research Associate, Department of Computer Science and Engineering, Michigan State University
- Aidan Murphy, Research Associate, Department of Computer SCience and Engineering, Michigan State University
Suggested for ages: Kindergarten and Pre-K, Elementary school age, Middle school age, High school age, 18 years and above
Scientific Disciplines:
- Physics, Astronomy, and Chemistry
- Engineering and Technology
- Science Education
- Mathematics
Time and Location
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4/14/2024 2:30 - 3:15 PM
Location: STEM Teaching and Learning Facility Room 1130