Mary Kathryn (Kate) Cowles
Professor of Statistics and Actuarial Science, College of Liberal Arts and Sciences
Professor of Biostatistics, College of Public Health
Primary Office: 241 Schaeffer Hall (SH)
The University of Iowa
Iowa City, IA 52242
The University of Iowa
Iowa City, IA 52242
Monday: 12:30 pm - 1:15 pm
Wednesday: 10:30 am - 11:15 am
Thursday: 1:30 pm - 2:15 pm
Kate Cowles received her Ph.D. in Biostatistics from the University of Minnesota. She is a Professor of Statistics and Biostatistics at The University of Iowa. Her research interests include Bayesian modeling, statistical computing, and environmental and spatial statistics.
- PhD in Biostatistics, University of Minnesota,, Minneapolis, Minnesota, United States, 1994
- MS in Biostatistics, University of Minnesota, Minneapolis, Minnesota, United States, 1990
- MM in Piano performance and pedagogy, Northwestern University, Evanston, Illinois, United States, 1972
- BA in Music, Carleton College, Northfield, Minnesota, United States, 1971
Areas of Research Interest
- Bayesian Statistics
- Computational Statistics
- Environmental and Spatial Statistics
Selected Professional Memberships
- American Statistical Association
Selected Awards and Honors
- President and Provost Award for Teaching Excellence,, The University of Iowa, 2015
- CLAS Collegiate Teaching Award, University of Iowa, 2011
- James N. Murray Faculty Award, University of Iowa, 2001
Selected Courses Taught
- Seminar Applied Statistics, STAT:7290, Spring 2018
- Readings in Statistics, STAT:6990, Spring 2018
- Reading Research, STAT:7990, Spring 2018
- Large Data Analysis, STAT:4740, Spring 2018
- Readings in Statistics, STAT:6990, Fall 2018
- Computing in Statistics, STAT:5400, Fall 2018
- Bayesian Statistics, STAT:4520, Fall 2018
- Cowles, M. (2018). Independent Sampling for Bayesian Normal Conditional Autoregressive Models with OpenCL Acceleration. Computational Statistics/Springer. DOI: https://doi.org/10.1007/s00180-017-0752-0.
- Liang, D., Cowles, M. & Linderman, M. (2016). Bayesian MODIS NDVI back-prediction by intersensor calibration with AVHRR. Remote Sensing of Environment, 186, 393-404. DOI: http://dx.doi.org/10.1016/j.rse.2016.09.002.
- Abban, B. K., Papanicolaou, A. N., Cowles, M., Wilson, C. G., Abaci, O., Wacha, K., Schilling, K. & Schnoebelen, D. (2016). An Enhanced Bayesian Fingerprinting Framework for Studying Sediment Source Dynamics in Intensively Managed Landscapes. Water Resources Research, 52, 4646-4673. DOI: 10.1002/2015WR018030.
- Cowles, M. K. (2013). Applied Bayesian Statistics with R and OpenBUGS Examples. Springer.
- Bayman, E. O., Chaloner, K. & Cowles, M. K. (2010). Detecting qualitative interaction: A Bayesian approach. Statistics in Medicine, 29(4), 455-463. DOI: 10.1002/sim.3787.
- Cowles, M., Yan, J. & Smith, B. J. (2009). Reparameterized and Marginalized Posterior and Predictive Sampling for Complex Bayesian Geostatistical Models. Journal of Computational and Graphical Statistics, 18(2), 262-282. DOI: 10.1198/jcgs.2009.08012.
- Smith, B. J., Yan, J., Cowles, M. (Eds.) (2008). Unified Geostatistical Modeling for Data Fusion and Spatial Heteroskedasticity with R Package ramps. Journal of Statistical Software, 25(10), 1-21. DOI: 10.18637/jss.v025.i10.
- Smith, B. J., Cowles, M. (2007). Correlating Point-Referenced Radon and Areal Uranium Data Arising from a Common Spatial Process. Journal of the Royal Statistical Society Series C -- Applied Statistics, 56(3), 313-326. DOI: 10.1111/j.1467-9876.2007.00579.x.
- Gaul, N. J., Cowles, M., Choi, K. K. & Lamb, D. (2016). Modified Bayesian Kriging for Noisy Response Problems for Reliability Analysis. (Vols. 2B). INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2015, VOL 2B.
- Cowles, M. K., Seedorff, M. & Sawyer, A. (2013). CARrampsOcl: Reparameterized and marginalized posterior sampling for conditional autoregressive models, OpenCL implementation.
- Cowles, M. (2016, July) Harnessing Heterogeneous Hardware for Affordable, Portable Bayesian Computing. Conference Presentation presented at Joint Statistical Meetings 2016, Chicago, Illinois.
- Cowles, M. (2013, April) Discussion of Revealing Latent Clusters from Dirichlet Process Mixture Models Using Product Partitions. Invited Lecture presented at SLAMM! 2013. Saint Louis Area Methods Meeting, Iowa City, Iowa.
- (2009, August) Reparameterized and Marginalized Posterior and Predictive Sampling for Complex Bayesian Geostatistical Models. Invited Lecture presented at Joint Statistical Meetings, American Statistical Association, Washington, District of Columbia.
- (2007, August) Bayesian Evaluation of Surrogate Endpints in Cinical Trials. Invited Lecture presented at Joint Statistical Meetings, American Statistical Association, Salt Lake City, Utah.
- (2007, June) Computing for Spatial Estimation and Prediction with Application to Residential Radon. Invited Lecture presented at DIMACS Workshop on Markov Chain Monte Carlo, DIMACS, Piscatway, New Jersey.
- (2006, April) Fusing Point-Referenced Radon Data with Areal Uranium Data Arising from a Common Process. Invited Lecture presented at Interface 2006, Interface of Statistics and Computing, Pasadena, California.
Selected Grants and Contracts
- Armstrong, Marc P (Principal Investigator), Cowles, Mary Kathryn (Co-Principal), Wang, Shaowen (Co-Principal) Grant Research/Creative Work (Applied or Basic). Grid-based Spatial Statistics Middleware: Theory, Design, Implementation, and Evaluation. Sponsored by University of Iowa Informatics Initiative. Completed. January 1, 2003 - December 31, 2003.
- Oliveira, Suely (Principal Investigator), Darcy, Isabel (Co-Principal), Stewart, David (Co-Principal), Cowles, Mary Kathryn (Co-Principal) Grant Equipment. EXTREEMS-QED: Large Data Analysis and Visualization. Sponsored by National Science Foundation. Funded. August 15, 2014 - August 14, 2019.
- Cowles, Mary (Principal Investigator), Bennett, David (Co-Principal), Kusiak, Andrew (Co-Principal), Segre, Alberto (Co-Principal), Stewart, Kathleen (Co-Principal) Grant Research/Creative Work (Applied or Basic). Integrated Graduate Research and Education Traineeship (IGERT): Geoinformatics for Environmental and Energy Modeling and Prediction (GEEMaP). Sponsored by National Science Foundation. Funded. July 1, 2010 - June 30, 2016.
Last Modified Date: January 6, 2020