Robert Kass
Robert E. Kass is the Maurice Falk Professor of Statistics and Computational Neuroscience in the Department of Statistics and Data Science, the Machine Learning Department, and the Neuroscience Institute at Carnegie Mellon University.
Robert E. Kass | |
---|---|
Born | Boston, Massachusetts, USA | September 7, 1952
Nationality | American |
Alma mater | University of Chicago (PhD) Antioch College (BA) |
Known for | Computational Neuroscience, Bayesian Statistics |
Awards | R. A. Fisher Lectureship, Elected to the National Academy of Sciences |
Scientific career | |
Fields | Statistics |
Institutions | Carnegie Mellon University |
Thesis | (1980) |
Doctoral advisor | Stephen Stigler |
Website | www |
Early life and education
Born in Boston, Massachusetts (1952), Kass earned a Bachelor of Arts degree in mathematics from Antioch College, and a PhD degree in Statistics from the University of Chicago in 1980, where his advisor was Stephen Stigler. Kass is the son of the late Harvard medical researcher Edward H. Kass[1] and stepson of the late Amalie M. Kass. His sister is the bioethicist, Nancy Kass.
Research and publications
Kass's early research was on differential geometry in statistics,[2] which formed the basis for his book Geometrical Foundations of Asymptotic Inference[3] (with Paul Vos), and on Bayesian methods. Since 2000 his research has focused on statistical methods in neuroscience.
Kass's best-known work includes a comprehensive re-evaluation of Bayesian hypothesis testing and model selection,[4][5] and the selection of prior distributions,[6] the relationship of Bayes and Empirical Bayes methods,[7] Bayesian asymptotics,[8][9] the application of point process statistical models to neural spiking data,[10][11] the challenges of multiple spike train analysis,[12][13] the state-space approach to brain-computer interface,[14] and the brain's apparent ability to solve the credit assignment problem during brain-controlled robotic movement.[15] Kass's book Analysis of Neural Data[16] (with Emery Brown and Uri Eden) was published in 2014. Kass has also written on statistics education and the use of statistics, including the articles, "What is Statistics?",[17] "Statistical Inference: The Big Picture,"[18] and "Ten Simple Rules for Effective Statistical Practice".[19]
Professional and administrative activities
Kass has served Chair of the Section for Bayesian Statistical Science of the American Statistical Association, Chair of the Statistics Section of the American Association for the Advancement of Science, founding Editor-in-Chief of Bayesian Analysis (journal), and Executive Editor (editor-in-chief) of the international review journal Statistical Science. At Carnegie Mellon University he was Department Head of Statistics from 1995 to 2004 and Interim Co-director of the joint CMU-University of Pittsburgh Center for the Neural Basis of Cognition 2015–2018.[20][21][22]
Honors
Kass is an elected Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science, and an elected member of the National Academy of Sciences. For his work on statistical modeling of neural synchrony,[23] in 2013 he received the Outstanding Statistical Application Award from the American Statistical Association, and in 2017 he received the R.A. Fisher Award and Lectureship, now known as the COPSS Distinguished Achievement Award and Lectureship, from the Committee of Presidents of Statistical Societies.
References
- "Edward H. Kass, M.D., Eulogy".
- Kass, Robert E. (1989). "The Geometry of Asymptotic Inference (with discussion)". Statistical Science. 4 (3): 188–234. doi:10.1214/SS/1177012480. S2CID 119728605 – via JSTOR.
- Kass, Robert E.; Vos, Paul (1997-03-07). Geometrical Foundations of Asymptotic Inference. doi:10.1002/9781118165980. ISBN 9780471826682.
- Kass, Robert E.; Raftery, Adrian (2012-02-27). "Bayes Factors". Journal of the American Statistical Association. 90 (430): 773–795. doi:10.1080/01621459.1995.10476572.
- Kass, Robert E.; Wasserman, Larry A. (1995). "A Reference Bayesian Test for Nested Hypotheses and its Relationship to the Schwarz Criterion". Journal of the American Statistical Association. 90 (431): 928–934. doi:10.1080/01621459.1995.10476592. S2CID 120491167 – via Taylor & Francis Online.
- Kass, Robert E.; Wasserman, Larry A. (1996). "The Selection of Prior Distributions by Formal Rules". Journal of the American Statistical Association. 91 (435): 1343–1370. doi:10.1080/01621459.1996.10477003. S2CID 53645083 – via Taylor & Francis Online.
- Kass, Robert E.; Steffey, Duane (2012-03-12). "Approximate Bayesian Inference in Conditionally Independent Hierarchical Models (Parametric Empirical Bayes Models)". Journal of the American Statistical Association. 84 (407): 717–726. doi:10.1080/01621459.1989.10478825.
- Kass, Robert E.; Tierney, Richard L. (1989). "Fully Exponential Laplace Approximations to Expectations and Variances of Nonpositive Functions". Journal of the American Statistical Association. 84 (407): 710–716. doi:10.1080/01621459.1989.10478824. S2CID 16075665 – via Taylor & Francis Online.
- Kass, Robert E., Tierney, Richard L. and Kadane, Joseph B. (1990) The validity of posterior expansions based on Laplace's method, Essays in Honor of George Bernard, eds. S. Geisser, J.S. Hodges, S.J. Press, and A. Zellner, Amsterdam: North Holland, 473-488.
- Kass, Robert E.; Ventura, Valerie (2001). "A spike-train probability model, Neural Computation". Neural Computation. 13 (8): 1713–1720. doi:10.1162/08997660152469314. PMID 11506667. S2CID 1840562 – via MIT Press Direct.
- DiMatteo, Illaria; Genovese, Christopher R.; Kass, Robert E. (2001-12-01). "Bayesian curve‐fitting with free‐knot splines". Biometrika. 88 (4): 1055–1071. doi:10.1093/biomet/88.4.1055.
- Brown, Emery N.; Mitra, Partha P.; Kass, Robert E. (2004-04-27). "Multiple neural spike train data analysis: state-of-the-art and future challenges". Nature Neuroscience. 7 (4): 456–461. doi:10.1038/nn1228. PMID 15114358. S2CID 562815.
- Kass, Robert E.; Ventura, Valerie; Brown, Emery N. (2005-07-01). "Statistical Issues in the Analysis of Neuronal Data". Journal of Neurophysiology. 94 (1): 8–25. doi:10.1152/jn.00648.2004. PMID 15985692.
- Brockwell, Anthony E.; Rojas, A.L.; Kass, Robert E. (2004-04-01). "Recursive Bayesian Decoding of Motor Cortical Signals by Particle Filtering". Journal of Neurophysiology. 91 (4): 1899–1907. doi:10.1152/jn.00438.2003. PMID 15010499.
- Jarosiewicz, Beata; Chase, Steven M.; Farser, George W.; Velliste, Meel; Kass, Robert E.; Schwartz, Andrew B. (2008-12-01). "Functional network reorganization during learning in a brain-computer interface paradigm". PNAS. 105 (49): 19486–19491. Bibcode:2008PNAS..10519486J. doi:10.1073/pnas.0808113105. PMC 2614787. PMID 19047633.
- Kass, Robert E.; Brown, Emery N.; Eden, Uri (2014). Analysis of Neural Data. Springer Series in Statistics. Wiley. doi:10.1007/978-1-4614-9602-1. ISBN 978-1-4614-9602-1.
- Kass, Robert E.; Brown, Emery N. (2008-09-01). "What Is Statistics?". The American Statistician. 63 (2): 105–110. doi:10.1198/tast.2009.0019. S2CID 120522019.
- Kass, Robert E. (2011-06-11). "Statistical Inference: The Big Picture". Statistical Science. 26 (1): 1–9. doi:10.1214/10-STS337. PMC 3153074. PMID 21841892.
- Kass, Robert E.; Caffo, Brian S.; Davidian, Marie; Meng, Xiao-Li; Reid, Nancy (2016-06-06). "Ten Simple Rules for Effective Statistical Practice". PLOS Comput Biol. 12 (6): e1004961. Bibcode:2016PLSCB..12E4961K. doi:10.1371/journal.pcbi.1004961. PMC 4900655. PMID 27281180.
- University, Carnegie Mellon. "Robert Kass - Statistics & Data Science - Dietrich College of Humanities and Social Sciences - Carnegie Mellon University". www.cmu.edu. Retrieved 2023-05-30.
- "Kass Elected to National Academy of Sciences – CNBC". Retrieved 2023-05-30.
- Email, Abby Simmons (2023-05-09). "Kass Elected to National Academy of Sciences - News - Carnegie Mellon University". www.cmu.edu. Retrieved 2023-05-30.
- Kass, Robert E.; Kelly, Ryan C.; Loh, Wei-Liem (2011-07-13). "Assessment of synchrony in multiple neural spike trains using loglinear point process models". The Annals of Applied Statistics. 5 (2B): 1262–1292. arXiv:1107.5872. Bibcode:2011arXiv1107.5872K. doi:10.1214/10-AOAS429. PMC 3152213. PMID 21837263.