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[Illinois] CSE 2013: Machine Learning and Cosmology: New Approaches to Constraining the Dark Universe

By Matias Carrasco Kind

University of Illinois at Urbana-Champaign

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Abstract


Bio

Matias Carrasco Kind, Astronomy

Currently Matias is a PhD student at the Astronomy Department and a CSE fellow at the University of Illinois at Urbana-Champaign (UIUC). He received his degree in Astronomy at Universidad Catolica de Chile (PUC) with highest honors, He did his undergraduate thesis at the Max-Planck Institute for Astrophysics (MPA) in Germany where he also spent some time doing PhD studies before working as an Adjunct professor for two years at the Universidad Andres Bello (UNAB) in Chile where he taught several physics courses.

Matias' main research interests are in cosmology and extragalactic astronomy, especially in large scale structure, galaxy formation and evolution, computational and theoretical cosmology, environmental dependence of galaxy properties, photometric redshift estimation, machine learning techniques and data mining among others.

(Source: https://publish.illinois.edu/mcarrasco/)

Cite this work

Researchers should cite this work as follows:

  • Matias Carrasco Kind (2013), "[Illinois] CSE 2013: Machine Learning and Cosmology: New Approaches to Constraining the Dark Universe," http://nanohub.org/resources/18165.

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Time

Location

NCSA Auditorium, University of Illinois at Urbana-Champaign, Urbana, IL

Submitter

NanoBio Node, Adeeb Yunus

University of Illinois at Urbana-Champaign

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