John C. Kern II
____________

Associate Professor of Statistics
____________

Department of Mathematics and Computer Science
____________

e-mail:
kern AT mathcs.duq.edu
____________

417 College Hall
Tele: (412)396-1835
Fax: (412)396-1937
 
 

page last modified
06/11/07

      BACKGROUND:

      I am an Associate Professor in the Department of Mathematics and Computer Science at Duquesne University. I earned my Ph.D. from the (then) Institute of Statistics and Decision Sciences at Duke University in 2000. In 1996, I graduated from Bucknell University with honors in mathematics (and a concentration in statistics).

      AWARDS AND HONORS include:

      Awarded the Duquesne University 2007 Presidential Award for Excellence in Teaching.

      Awarded the 2006--2007 Excellence in Teaching Award for the McAnulty College of Liberal Arts.

      During the 2006 and 2007 summers I was a reader for the AP statistics examination.

      During the 2002 through 2005 summers I was a visiting faculty at the Los Alamos National Laboratory and conducted research there in the Statistical Sciences group.

      Earned the rank of Eagle Scout in the summer of 1992.

      TEACHING INTERESTS:

      MA 301: Introduction to Probability. Introducing mathematics majors to probability, ahh yes. Goes great with Douglas Kelly's text whose title matches that of this course.

      MA 302W: Introduction to Statistics. Teaching the logic of hypothesis testing, introducing the Bayesian paradigm, and best of all, data analysis reports in LaTeX.

      CPMA 573: Statistical Computing. Introducing math/computer science graduate students to Monte Carlo integration/simulation and its role in Bayesian inference. Other techniques for inference in classical models (e.g. multivariable Newton-Raphson) are also covered.

      All other statistics/mathematics courses I have taught (about eight others, including calculus I and II) are great too; these three seem to inspire me the most, though. Since I have not yet taught all statistics/mathematics courses offered by the department of mathematics and computer science here at Duquesne, I may be updating the above list without warning. Finally, I have chosen to make use of the Blackboard course-enhancement technology offered by Duquesne; therefore no web-links to the courses I teach are provided here.

      RESEARCH INTERESTS:

      Bayesian methodology and computation, and its application to: Spatial Statistics, Clinical Trials, Software Testing, Health Insurance, Knot Theory, and Pass the Pigs.

      Cross-disciplinary research efforts. The Center for Computational Sciences here at Duquesne fosters research collaboration among professors in chemistry, biology, mathematics, computer science and physics.

      PUBLICATIONS:

      Kern, J.C., Ghosh, S.K., and Bernini, N. Bayesian analysis of multi-subject longitudinal data: a comparison of models. In preparation.

      Kern, J.C., Kingston, S. and Sun, J. The mathematics behind speciated isotope dilution mass spectrometry. In preparation.

      Kern, J.C., and Graves, T.L. Software testing using Bayesian logistic regression and the gamma point-mass distribution. Back burner, almost falling off of the stove.

      Rutkowski, J.J., Fennell, J.W., Kern II, J.C., Madison, D.E., and Johnson, D.A. (2007). Inhibition of Alveolar Osteitis in mandibular tooth extraction sites using Platelet Rich Plasma (PRP). Journal of Oral Implantology, Vol 33, 3, pages 116--121.

      Plunkett, P., Piatek, M., Dobay, A., Kern., J.C., Millett, K.C., Stasiak, A., Rawdon, E.J. (2007). Total Curvature and Total Torsion of Knotted Polymers. Macromolecules, 40(10) pages 3860--3867.

      Kern, J.C. (2006). Pig Data and Bayesian Inference on Multinomial Probabilities. Journal of Statistics Education, Volume 14, Number 3 (~15 pages). www.amstat.org/publications/jse/v14n3/datasets.kern.html

      Kern, J.C., and Cohen, S.M. (2005). Menopausal symptom relief with acupuncture: modeling longitudinal frequency data. Communications in Statistics: Simulation and Computation, Vol 34, 3, pages 783--798.

      Rahman, G.M., Kingston, H.M., Kern, J.C., Hartwell, S.W., Anderson, R.F., and Yang, S. (2005). Inter-laboratory validation of EPA method 3200 for mercury speciation analysis using prepared soil reference materials. Applied Organometallic Chemistry, 19, pages 301--307.

      Graves, T.L., and Kern, J.C. (2003). Software testing and reliability modeling for Army Systems. Los Alamos National Laboratory Report LA-UR-03-0077.

      Higdon, D.M., Swall, J., and Kern, J.C. (1999). Non-stationary spatial modeling. In Bayesian Statistics 6. Oxford University Press, pages 761--768.

      Kern, J.C., and Higdon, D.M. (1999). A distance metric to account for edge effects in spatial data analysis. In 1999 ASA Proceedings of the Biometrics Section, pages 49-52.

      Frey, M. and Kern, J.C. (1997). The Pitman closeness of a class of scaled estimators. The American Statistician, Vol. 51, Number 2, pages 151--154.

      LINKS OF INTEREST:

      A listing of the Master's students I have advised and their research.

      A list of the undergraduate research projects I have advised.

      An infrequently updated list of the research talks and presentations I have given.

      Information on YADAS, a JAVA-based data analysis system designed by Todd Graves at Los Alamos National Laboratory.