معرفی
Karianne Bergen is an Assistant Professor of Data Science and Earth, Environmental & Planetary Sciences at Brown University, with a courtesy appointment in Computer Science. She leads the Scientific Machine Learning (SciML) Research Group, affiliated with the Data Science Institute (DSI), DEEPS, and the SciAI Center. Her research focuses on scientific machine learning (SciML), including surrogate models for climate science, explainable AI (XAI), and foundation models. She holds a Ph.D. and M.Sc. in Computational and Mathematical Engineering from Stanford University and a B.Sc. in Applied Mathematics from Brown University. Her postdoctoral training included a Harvard University HDSI fellowship in Computer Science.
Education:
- B.Sc. Applied Mathematics, Brown University (2009)
- M.Sc. Computational and Mathematical Engineering, Stanford University (2015)
- Ph.D. Computational and Mathematical Engineering, Stanford University (2018)
Research Interests: Dr. Bergen’s work bridges machine learning and Earth sciences, emphasizing scalable methods for climate modeling and geophysical data analysis. Her group develops emulators for Antarctic ice sheet dynamics, XAI frameworks for climate data interpretation, and scientific foundation models for geoscience applications. Recent projects include GAN-based sea ice resolution enhancement and flow-based neural networks for sea level projections.
Awards:
- Harvard Data Science Initiative Postdoctoral Fellowship (2018–2020)
- Stanford Graduate Fellowship in Science and Engineering (2011–2015)
- Outstanding Student Paper Award, American Geophysical Union (2015)
Advising & Collaborations: She mentors PhD students in Earth, Environmental, and Planetary Sciences and collaborates with institutions like MIT-Lincoln Laboratory, SciAI Center, and international geoscience groups. Her lab includes postdocs (e.g., Hilarie Sit) and alumni from data science practicum programs.
Labs/Teams: The SciML group at Brown University focuses on multidisciplinary projects at the intersection of AI and Earth sciences, with recent presentations at AGU Fall Meetings and the AI for Science Workshop at ICML.
