I am a Data Science Initiative Postdoctoral Fellow at Harvard University. I am affiliated with the School of Engineering and Applied Sciences (SEAS/Computer Science) and Department of Earth and Plantary Sciences (EPS).

My research interest is in scientific machine learning. 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 earned my Ph.D in Computational and Mathematical Engineering at Stanford University, where I was advised by Greg Beroza, Professor of Geophysics. Prior to starting my graduate studies, I worked as a research data scientist in the Biodefense Systems group at MIT-Lincoln Laboratory. I hold a B.Sc. in Applied Mathematics from Brown University and a M.S. in Computational and Mathematical Engineering from Stanford University.

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.

This portfolio contains information about my professional work, including my research projects and teaching experiences.

Thanks for visiting!

Karianne

Fall 2019 - I'm on the job market (junior faculty or research scientist roles)!

Application materials are available here.

News:

Upcoming Events:

  • Dec 9-13, 2019: AGU Fall Meeting in San Francisco, CA.
    • Oral Presentation (S53A-03): "How robust is deep learning-based earthquake detection? Insights from adversarial machine learning," Friday, December 13 at 2:10pm, Moscone South 158

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