Murali Haran ^{ pronunciation }

Professor and Head, Department of Statistics, Penn State University

Office: 421D Thomas

Phone: 814-863-8126

Appointments: sign up online (primarily for undergrad advisees but others are welcome to use this)

B.S. Computer Science (minors: statistics, mathematics and film), Carnegie Mellon U. 1997.

M.S., Ph.D. Statistics, University of Minnesota, 2003.

Postdoctoral fellow, NISS (courtesy appointment at Duke University) (2003--2004).

New Research Fellow, SAMSI (2009--2010); Visitor, Fall 2017.

Visiting Associate Professor (2011--2012) Statistics, University of Washington.

Teaching

- Computationally-intensive Probability and Statistics, Fall 2019
- Data Science through Statistical Reasoning and Computation, Spring 2018
- Courses Taught in Previous Semesters

Primary Research Interests

- Statistical computing, primarily Markov chain Monte Carlo algorithms
- Models for spatial data: Gaussian random field models, Bayesian hierarchical models
- Complex computer models/computer experiments: statistical emulation and calibration
- Cross-disciplinary research in environmental sciences: climate science, disease modeling, ecology

CV and Short bio

Dr. Murali Haran is Professor and Head of the Department of Statistics at Pennsylvania State University. He has a PhD in Statistics from the University of Minnesota, and a BS in Computer Science from Carnegie Mellon University. His research interests are in Monte Carlo algorithms, spatial models, statistical analysis of complex computer models, and interdisciplinary work in climate science and infectious diseases.

Longer bio also has a list of current and former graduate students.

Advice/mentoring

Haran, M., Bandeen-Roche, K., Horton, N., Johnson, G., and Kim, M. (2019) Advice for New FacultyAmstat News, July 2019based on a NISS webinar video on YouTube .

Haran, M. and Hunter, D.R. (2016) On Academic MentoringAmstat News, September 2016.

Selected Papers(link to longer list of publications and google scholar references ) andcurrent CV

- Park, J. and Haran, M. (2018) Bayesian Inference in the Presence of Intractable Normalizing Functions , accepted for publication in the
Journal of the American Statistical Association

- Chang, W., Haran, M., Applegate, P., and Pollard, D. (2016) Calibrating an ice sheet model using high-dimensional binary spatial data ,
Journal of the American Statistical Association, 111, 513, 27-72

- Goldstein, J., Haran, M., Simeonov, I., Fricks, J., and Chiaromonte, F. (2015) An attraction-repulsion point process model for respiratory syncytial virus infections
Biometrics, 71, 2, pp 376--385(Winnerof student paper competition at the Graybill/ENVR 2014 conference)

- Chang, W., Haran, M., Olson, R., and Keller, K. (2014) Fast dimension-reduced climate model calibration and the effect of data aggregation,
Annals of Applied Statistics,8, 2, pp 649--673. (Winner of the 2014 American Statistical Association Section on Statistics and the Environment Student Paper Competition)

- Jandarov, R., Haran, M., Bjornstad, O.N. and Grenfell, B.T. (2014) Emulating a gravity model to infer the spatiotemporal dynamics of an infectious disease
Journal of the Royal Statistical Society, Series C, 63, 3, pp. 423--444.

- Katz, R.W., Craigmile, P.F., Guttorp, P., Haran, M., Sanso, B. and Stein, M.L. (2013) Uncertainty Analysis in Climate Change Assessments ,
Nature Climate Change, 3, pp. 769--771.

- Hughes, J. and Haran, M. (2013), Dimension Reduction and Alleviation of Confounding for Spatial Generalized Linear Mixed Models ,
Journal of the Royal Statistical Society, Series B, 75, 1, 139--159.

Software for this approach may be found here: ngspatial

- Tingley, M., Craigmile, P.F., Haran, M., Li, B., Mannshardt-Shamseldin, E. and Rajaratnam, B. (2012), Piecing together the past: Statistical insights into paleoclimatic reconstructions ,
Quaternary Science Reviews, 35, 1--22.

- Haran, M. (2011) Gaussian random field models for spatial data, in
Handbook of Markov chain Monte Carlo,Editors, Brooks, S.P., Gelman, A.E. Jones, G.L. and Meng, X.L., Springer-Verlag. bibtex

- Hughes, J.P., Haran, M., and Caragea, P.C. (2011), Autologistic models for binary data on a lattice ,
Environmetrics, 7, 857--871.

- Flegal, J.M., Haran, M., and Jones, G.L. (2008) Markov chain Monte Carlo: Can we trust the third significant figure?
Statistical Science,23,250--260. bibtex

Code for consistent batch means estimator for MCMC standard errors as described in the paper: R package on CRAN , R function and C function

- Jones, G.L., Haran, M., Caffo, B.S. and Neath, R. (2006) Fixed Width Output Analysis for Markov chain Monte Carlo
, Journal of the American Statistical Association, 101:1537--1547.bibtex

- Ph.D. Theses: current and past students
- M.S. Theses: current and past students
- B.S./Honors Theses: current and past students

SMAC (Stochastic Modeling and Computing) Seminar Series

Other Roles

- Co-Editor:
Bayesian Analysis (2016--2018)- Associate editor:
The American Statistician (2015--present). (Past) associate editorJournal of Agricultural, Biological and Environmental Statistics (2010--2015); Biometrics (2009--2011); Bayesian Analysis (2010--2015)- Schreyer Honors College adviser for Statistics and Honors College thesis adviser
- Chair of the
American Statistical Association (ASA) Section on Risk Analysis2013-2014- Treasurer for the International Society for Bayesian Analysis ( ISBA ) 2014--2016
- (Past) Chair of the Penn State Statistics Undergraduate Program: 2012--2016
- Climate Science Related Roles:

- Co-leader for Uncertainty Quantification Group in the NSF network SCRiM (Sustainable Climate Risk Management), multi-institution network with Penn State as the hub
- PI on NSF-CDSE grant Statistical Methods for Ice Sheet Projections using Large Non-Gaussian Space-time Data Sets and Complex Computer Models, 7/01/2014--6/30/2017.
- Director of the Penn State Node of the NSF research network STATMOS , Statistical Methods for Atmospheric and Oceanic Sciences.
- Member of the ASA Advisory Committee on Climate Change Policy 2009--2014
- Co-Director of CLIMA Center for Climate Risk Management at Penn State.

General articles on statistics:STATISTICS-AT-LARGE

Everything Else:NON-ACADEMIC