Matias Carrasco Kind

Director of Data Science Research Services and Research Assistant Professor of Accountancy

Contact

3052 Business Instructional Facility

515 Gregory Dr

Champaign, IL 61820

Ph.D., Astrophysics, University of Illinois at Urbana-Champaign, 2014
M.S., Astrophysics, University of Illinois at Urbana-Champaign, 2011
B.S., Summa Cum Laude, Astronomy, Pontificia Universidad Catolica de Chile, 2005

Affiliate Professor, National Center for Supercomputing Applications, 2021 to present
Director of Data Sciences Research Services, Data Science Research Services (DSRS),, University of Illinois at Urbana-Champaign, 2021 to present
Research Assistant Professor of Accountancy, Accountancy, University of Illinois at Urbana-Champaign, 2021 to present
Assistant Director of Data Sciences Research Services, Data Science Research Services,, University of Illinois at Urbana-Champaign, 2020-2021
Research Assistant Professor, Department of Astronomy, University of Illinois at Urbana-Champaign, 2019 to present
Senior Research Scientist, National Center for Supercomputing Applications (NCSA), University of Illinois at Urbana-Champaign, 2018 to present
Research Scientist, National Center for Supercomputing Applications (NCSA), University of Illinois at Urbana-Champaign, 2014-2018
Adjunct Professor and Research Scientist, Universidad Andres Bello, Chile, 2008-2010
LENAC/ALPHA Visitor/Fellow, Max Planck Institute for Astrophysics, 2006

Asorey, J., Carrasco Kind, M., Sevilla-Noarbe, I., Brunner, R., & Thaler, J. (2016). Galaxy clustering with photometric surveys using PDF redshift information. Monthly Notices of the Royal Astronomical Society, Oxford University Press, 459 (2), 1293--1309.
Kim, E., Brunner, R., & Carrasco Kind, M. (2015). A hybrid ensemble learning approach to star--galaxy classification. Monthly Notices of the Royal Astronomical Society, Oxford University Press, 453 (1), 507--521.
Carrasco Kind, M., & Brunner, R. (2015). SparsePZ: Sparse Representation of Photometric Redshift PDFs. Astrophysics Source Code Library, ascl--1511.
Carrasco Kind, M., & Brunner, R. (2014). Exhausting the information: novel Bayesian combination of photometric redshift PDFs. Monthly Notices of the Royal Astronomical Society, Oxford University Press, 442 (4), 3380--3399.

Carrasco Kind, M., & Brunner, R. (2014). MLZ: Machine Learning for photo-Z. Astrophysics Source Code Library, ascl--1403.
Carrasco Kind, M., & Brunner, R. (2014). SOM z: photometric redshift PDFs with self-organizing maps and random atlas. Monthly Notices of the Royal Astronomical Society, Oxford University Press, 438 (4), 3409--3421.
Carrasco Kind, M., & Brunner, R. (2014). Sparse representation of photometric redshift probability density functions: preparing for petascale astronomy. Monthly Notices of the Royal Astronomical Society, Oxford University Press, 441 (4), 3550--3561.
S\'anchez, C, ., Carrasco Kind, M., Lin, H., Miquel, R., Abdalla, F., Amara, A., Banerji, M., Bonnett, C., Brunner, R., Capozzi, D., & others, . (2014). Photometric redshift analysis in the Dark Energy Survey science verification data. Monthly Notices of the Royal Astronomical Society, Oxford University Press, 445 (2), 1482--1506.
Carrasco Kind, M., & Brunner, R. (2013). Implementing Probabilistic Photometric Redshifts. Astronomical Data Analysis Software and Systems XXII, 475 69.
Carrasco Kind, M., & Brunner, R. (2013). TPZ: photometric redshift PDFs and ancillary information by using prediction trees and random forests. Monthly Notices of the Royal Astronomical Society, The Royal Astronomical Society, 432 (2), 1483--1501.

Yu, W., Carrasco Kind, M., & Brunner, R. (2017). A Jupyter-based Interactive Visualization Tool for Astronomical Catalogs. American Astronomical Society Meeting Abstracts\# 229 ( vol. 229, pp. 438--02).
Carrasco Kind, M., & Brunner, R. (2013). Precision Cosmology with a New Probabilistic Photometric Redshifts Approach. American Astronomical Society Meeting Abstracts ( vol. 222, pp. 119--01).

3052 Business Instructional Facility

515 Gregory Dr

Champaign, IL 61820