Welcome to Karianne's Website!
I am an Assistant Professor of Data Science and Earth, Environmental & Planetary Sciences and Assistant Professor of Computer Science at Brown University.
My research interest is in scientific machine learning (SciML). My past work has focused on machine learning for pattern recognition and discovery in large, noisy sensor data sets, with applications in earthquake seismology and biodefense.
I did my postdoctoral training at Harvard University as a Data Science Initiative Postdoctoral Fellow in Computer Science. I earned my Ph.D (and M.S.) in Computational and Mathematical Engineering at Stanford University, and my B.Sc. in Applied Mathematics from Brown University. I have also worked as a data scientist at MIT-Lincoln Laboratory.
I am also passionate about data science education and diversity and inclusion in data science. I have taught a number of courses and workshops that aim to make data science accessible to students and professionals from a range of disciplinary backgrounds.
Thanks for visiting!
June 2022: Summary of our review paper (below) available on Eos: The Big Data Revolution Unlocks New Opportunities for Seismology.
April 2022: Review paper Big Data Seismology, lead by Stephen Arrowsmith, accepted for publication in Reviews of Geophysics.
April 2022: SciML Ph.D. student Peter Van Katwyk has been awarded the NSF Graduate Research Fellowship in Geosciences - Artificial Intelligence. Congratulations Peter!
Jan 2022: TWIML AI podcast interview: Machine Learning for Earthquake Seismology with Karianne Bergen [episode page] [watch on YouTube]
Nov 2022: NSF AI Planning Institute for Data-Driven Discovery in Physics Seminar Series, Carnegie Mellon [virtual]
Nov 2022: Earthquake Science Center Seminar, USGS.
Sept 2022: Artificial Intelligence Applications in Earthquake Engineering, EERI San Diego Chapter [virtual]
August 2022: International Symposium, Frontier of Understanding Earth's Interior and Dynamics, Sendai, Japan [virtual]
March 2022: Seminars at University of Montana and University of Oslo.
Dec 2021: Invited panelist, AI for Science: Mind the Gaps Workshop at NeurIPS.
Dec 2021: AGU Fall Meeting (virtual) talk: Explainable AI (XAI) for Seismology: An interpretable convolutional neural network for earthquake detection [a recording of this talk is available by request]
More details on the Presentations page