Dr. Karianne Bergen

Assistant Professor

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Biography

Karianne Bergen is an Assistant Professor in the Department of Data Science and the Department of Earth, Environmental, and Planetary Sciences at Brown University. Her research focuses on scientific machine learning (SciML), with a particular emphasis on pattern recognition and data analysis of large, complex sensor datasets. Her work includes applications in earthquake seismology and biodefense. Currently, her research group is investigating machine learning-based surrogate models for data enhancement, explainable AI for scientific data, and the development of scientific foundation models. She holds a Sc.B. in Applied Mathematics from Brown University, and both an M.Sc. and a Ph.D. from Stanford University. Additionally, she completed her postdoctoral training in Computer Science at Harvard University's Data Science Initiative. Before joining Brown, she worked as a data scientist at MIT Lincoln Laboratory.

Research Interests

Experience

Data Scientist (Research)

2009-01-01 — 2011-01-01

MIT Lincoln Laboratory • Cambridge, MA

Conducted research and development in data science.

Postdoctoral Fellow

2018-01-01 — 2020-01-01

Harvard University, Data Science Initiative • Cambridge, MA

Focused on scientific machine learning and data science.

Awards

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Harvard Data Science Initiative Postdoctoral Fellowship

2018-01-01
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Student Leadership Award

2018-01-01
#

Student Author Award

2018-01-01
#

Student Presentation Award

2016-01-01
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Outstanding Student Paper Award

2015-01-01

Courses

Machine Learning Earth Environment Tackling Climate Change with Machine Learning Data Detectives: Think Like a Data Scientist Probability, Statistics, and Machine Learning

Requirements for Brown University

Doctorate Program
Requirements
GRE General
TOEFL
Total
Required:90
IELTS
Overall
Required:7
Prerequisites
Undergraduate degree in Economics or related field
Application Checklist
  • Personal Statement
  • Transcripts
  • 3 Letters of Recommendation
  • GRE Scores
  • TOEFL/IELTS Scores (if applicable)
Specialization Notes

Department: Department of Economics