U.S. Environmental Protection Agency	Voice: (919) 541-7655
MD E243-01	Fax: (919) 541-1379
Research Triangle Park, NC 27711 USA	Swall.Jenise@epa.gov

Professional experience

U.S. Environmental Protection Agency, Research Triangle Park, NC

Develop and apply statistical methods appropriate for evaluating the performance of air quality models and for assessing air quality trends.

Conduct research as a member of various interdisciplinary teams and advise atmospheric scientists, meteorologists, and other environmental scientists on statistical and numerical issues that arise in the course of larger research efforts.

Advise individual scientists and project teams on statistical matters, such as appropriate techniques for inference and interpretation of the results of statistical procedures, and on statistical computing issues, including selection of statistical software packages and appropriate use of statistical algorithms.

Kenyon College, Gambier, OH
Assistant Professor of Mathematics, July 2001-June 2003

Developed and taught courses in elementary statistics, data analysis, design and analysis of experiments, probability, and mathematical statistics. (Teaching load: 2-3 courses per semester)

Continued research into non-stationary spatial models, with an emphasis on incorporation of censored data, model comparison, Markov chain Monte Carlo (MCMC) convergence issues, and improvement of computational efficiency.

Responsible for providing own UNIX system administration, maintenance, and back-ups.

Los Alamos National Laboratory, Los Alamos, NM
Visiting Faculty Program, June 2002-July 2002

Developed model comparison methodologies for various spatial modeling strategies. Contributed to other on-going projects at LANL.

Duke University, Durham, NC
Visiting Assistant Professor, January 2000-June 2001

Designed and taught a new calculus-based statistics course for economics majors, with an enrollment of over 100 students each semester. Developed an archive of teaching materials for use by future faculty teaching this course.

Continued research into non-stationary spatial processes, with a particular emphasis on modeling correlation dependence structure as a mixture of a set of weighted "basis" kernels. Increased computational efficiency beyond that achieved by many previous methods, without requiring assumptions of stationarity or isotropy.

SAS Institute, Cary, NC
Assistant Applications Developer, June 1996-August 1997

Served as member of consulting team on variety of projects, including applications in banking, human resources management, and educational administration. Designed and implemented SAS software solutions for clients, with emphasis on providing user-friendly interfaces, maintaining data security, managing databases, generating reports easily and efficiently.

Education

Duke University, Durham, NC

Massachusetts Institute of Technology, Cambridge, MA
B.S. in Mathematics (applied emphasis), May 1994

Completed degree in three years.

Research interests

Bayesian statistics, statistical computing, statistics in environmental applications, modeling spatial processes

Selected publications

1. Swall, J. L., Foley, K. M., 2009. The impact of spatial correlation and incommensurability on model evaluation. Atmospheric Environment, Vol. 43, No. 6, 1204-1217. (abstract)
2. Irwin, J., Civerlo, K., Hogrefe, C., Appel, K., Foley, K., Swall, J., 2008. A procedure for inter-comparing the skill of regional-scale air quality model simulations of daily maximum 8-hour ozone values. Atmospheric Environment, Vol. 42, No. 21, 5403-5412. (abstract)
3. Cooter, E., Gilliam, R., Swall, J., Mickley, L. Comparison of current U.S. global reanalysis 700 hPa wind patterns to downscaled climate model results using cluster analysis. (in revision)
4. Cooter, E., Gilliam, R., Swall, J. Comparison of downscaled current and future 700 hPa wind patterns using cluster analysis. (in revision)
5. Cooter, E., Gilliam, R., Benjey, W., Nolte, C., Swall, J., Gilliland, A. Examining the impact of changing climate on regional air quality over the U.S. Developments in Environmental Sciences, Chp. 6.1, Vol. 6, 2007. (abstract)
6. Cooter, E., Swall, J., Gilliam, R., 2007. Comparison of 700 hPa NCEP-R1 and AMIP-R2 wind patterns over the continental U.S. using cluster analysis. Journal of Applied Meteorology and Climatology, Vol. 46, No. 11, pp. 1744-1758.
7. Zheng, J., Swall, J. L., Cox, W. M., Davis, J. M., 2007. Interannual variation in meteorologically adjusted ozone levels in the eastern United States: a comparison of two approaches. Atmospheric Environment, Vol. 41, No. 4, 705-716. (abstract)
8. Koracin, D., Panorska, A., Isakov, V., Touma, J., Swall, J.., 2007. A statistical approach for estimating uncertainty in dispersion modeling: An example of application in southwestern U.S. Atmospheric Environment, Vol. 41, No. 3, 617-628. (abstract)
9. Swall, J. L. Davis, J. M., 2006. A Bayesian statistical approach for the evaluation of CMAQ. Atmospheric Environment, Vol. 40, No. 26, 4883-4893. (abstract)
10. Ching, J., Herwehe, J., Swall, J., 2006. Paradigm using joint deterministic grid modeling and sub-grid variability stochastic descriptions as a template of model evaluation. Atmospheric Environment, Vol. 40, No. 26, 4935-4945. (abstract)
11. Hogrefe, C., Porter, P.S., Gego, E., Gilliland, A., Gilliam, R., Swall, J., Irwin, J., Rao, S.T, 2006. Temporal features in observed and predicted meteorology and air quality over the Eastern United States. Atmospheric Environment, Vol. 40, No. 26, 5041-5055. (abstract)
12. Davis, J. M., Swall, J. L., 2006. An examination of the CMAQ simulations of the wet deposition of ammonium from a Bayesian perspective. Atmospheric Environment, Vol. 40, No. 24, 4562-4573. (abstract)
13. Yu, S., Dennis, R., Roselle, S., Nenes, A., Walker, J., Eder, B., Schere, K., Swall, J., Robarge, W., 2005. An assessment of the ability of 3-D air quality models with current thermodynamic equilibrium models to predict aerosol NO₃^-. Journal of Geophysical Research, 110, D07S13. (abstract)
14. Swall, J. L., 1999. Non-stationary spatial modeling using a process convolution approach, Ph.D. Dissertation, Duke University
15. Higdon, D., Swall, J., Kern, J. Non-Stationary Spatial Modeling. Bayesian Statistics 6, Oxford University Press, 1999

Recent presentations

"Statistical Issues in the Assessment of Air Quality Model Performance"

Invited talk, Virginia Tech Dept. of Statistics, September 2009

"Spatio-Temporal Modeling of Air Pollutants Using a Process Convolution Approach"

Contributed talk, Joint Statistical Meetings, August 2009

"The Impact of Spatial Correlation and Incommensurability on Model Evaluation" (joint work with Kristen Foley)

Invited talk, EPA Data Analysis Workgroup, March 2009

Professional service

Member, Atmospheric Environment editorial advisory board, Jan. 2008 - present

Invited session co-organizer (with Kristen Foley), Joint Statistical Meetings 2009

"From Data to Decisionmaking: Applied Statisticians Protecting the Environment", August 2009

Session chair, Joint Statistical Meetings 2009

"Modeling Seasonal Data in Environmental Studies", August 2009

Committee on Student Awards and Travel Fellowships, Section on Statistics and the Environment, American Statistical Association

Chair, 2007

Member, 2005-2007

Reviewer

Atmospheric Environment

Ecology

Journal of Environmental Management

Journal of the American Statistical Association

Statistical Science

Professional organizations

American Statistical Association

Section on Bayesian Statistical Science

Section on Statistics and the Environment

Section on Statistical Computing

Computing

Operating systems: Linux/UNIX, Windows, Mac OS
Programming languages: C, R, S-Plus, SAS
Document preparation: LaTeX, Microsoft Office, HTML