University of the Sciences in Philadelphia

Laura Pontiggia, PhD

Education:

Ph.D, Statistics, University of Minnesota, Minneapolis
M.S., Statistics, University of Minnesota, Minneapolis
Doctor of Economics Summa Cum Laude, University of Pavia, Italy

Prior Positions:

• Adjunct Assistant Professor, University of the Sciences, Department of Health Policy and Public Health, Fall 2006
• Visiting Assistant Professor, University of Minnesota, 2004-2005
• Post-Doctoral Fellowship, Politecnico di Milano, Italy, 2002-2003

Background:

Dr. Pontiggia’s original research interest is non-cooperative stochastic games. In particular she has been studying variations of a two-person, non-cooperative stochastic game, inspired by the famous red-and-black gambling problem presented by Dubins and Savage. Currently, her major interest in game theory concerns developing a cooperative game theory approach to classification analysis, based on the use of the Shapley Value imputation. Her newest research interest concerns statistical methods for pharmaceutical and public health research. In particular she is working on the development of statistical methods that can be used to model data originated in the pharmaceutical and public health fields.

Research Interests:

• Non-cooperative stochastic games
• A cooperative game theory approach to classification analysis
• Models for biological data
• Statistical approaches for clinical and pharmaceutical data
• Models for health sciences data
• Educational research

Membership in Professional Organizations

• American Statistical Association (ASA)
• Institute of Mathematical Statistics (IMS)
• International Statistical Institute (ISI)
• Game Theory Society (GTS)
• Interanational Association for Statistical Education (IASE)

Publications:

P. Blumberg and L. Pontiggia (2010) Benchmarking the learner-centered status of courses, accepted by Innovative Higher Education.

J. Joseph, R. Fiscella, K. Rodvold, L. H. Danziger, M. Blair, L. Ulanski, J. Stokes, M. J. Shapiro, N. Blair, and L. Pontiggia (2010) Aqueous and vitreous penetration of linezolid and levofloxacin after oral administration, accepted by Journal of Ocular Pharmacology and Therapeutics.

R. A. Smith, L. Pontiggia, C. Waterman and M. Lichtenwalner (2010) Introducing experimental design by evaluating efficacy of herbal remedies, Journal of Biological Education, 44, 4, 175-179.

C. Waterman, R. Smith, L. Pontiggia, and A. DerMarderosian (2010) Anthelmintic screening of Sub-Saharan African plants used in traditional medicine, Journal of Ethnopharmacology, 127, 3, 755-759.

J. Reinhold, L. Pontiggia, M. Angeles, and G. Earl (2010) Web-based instruction on substance abuse and drug diversion, American Journal of Pharmaceutical Education, 74, 4, Article 57.

R. A. Smith, L. Pontiggia, C. Waterman, M. Lictenwalner, and J. Wasserman (2009) Comparison of motility, recovery, and methyl-thiazolyl-tetrazolium reduction assays for use in screening plant products for anthelmintic activity, Parasitology Research, 105, 5, 1339-1343, DOI: 10.1007/s00436-009-1560-4.

S. Alsardary, M. Hamid, L. Pontiggia and P. Blumberg (2009) Assessing the interactive, learner-centered methods of teaching mathematics, accepted by PRIMUS.

L. Pontiggia (2007) Non-constant sum red-and-black games with bet-dependent win probability function, Journal of Applied Probability, 44, 2.

A.M. Paganoni and L. Pontiggia (2007) Laboratorio di Statistica con Excel, Pearson Education.

L. Pontiggia (2005), Two-person red-and-black with bet-dependent win probabilities, Advanced Applied Probability, 37, 75-89

Teaching Responsibilities

Undergraduate courses:

• ST310 Intro to Biostatistics
• ST331 Regression Analysis
• ST332 Design and Analysis of Experiments
• ST335 Statistics for Clinical Trials
• ST340 SAS programming and Data Analysis
• ST490 Special Topics in Applied Biostatistics

Graduate courses:

• ST704 Statistics for Research
• ST710 Biostatistical Methods
• HE710 Statistics for Public Health
• HP750 Intro to Statistical Methods
• ST701 Design and Analysis of Experiments
• ST720 Regression Analysis
• ST711 SAS Programming and Data Analysis
• ST715 Statistics for Clinical Trials