Dr. Amanda Hepler is an experienced consultant providing expertise in statistics, Bayesian networks, evidential analysis, statistical genetics and computer programming. Dr. Hepler brings seven years of academic research experiences and is established among the forensic statistics community as a strong proponent of the use of likelihood ratios for the evaluation of forensic evidence. During her tenure as an Intelligence Community Postdoctoral Fellow, her research team developed likelihood ratio methods for biometric handwriting identification and for assessing the probative value of handwritten evidence in forensic casework. Throughout her academic career, Dr. Hepler has successfully presented complex statistical methods and probabilistic arguments to audiences with varied backgrounds, including lawyers, forensic scientists, politicians, engineers and statisticians. She has enjoyed developing and teaching a three-day training course entitled Forensic Statistics.
Since joining IDI, Dr. Hepler has worked closely with the Navy’s program directors in both the Safety and Occupational Health and Fire and Emergency Services programs to develop physical and financial resource estimation models, providing decision support to program managers seeking cost effective solutions that meet customer needs. She also serves as a consulting statistician on IDI’s Calibrated Baseline Model Project for the Navy’s Operational Logistics Energy Conservation office. The team has developed statistical models of vessel energy consumption to produce high quality forecasts of energy conservation initiative effectiveness and assess efficacy of installed initiatives. Dr. Hepler is currently supporting the customers intelligence community, measuring mission effectiveness of future systems and quantifying uncertainty reduction. Dr. Hepler has extensive programming experience, with proficiency in a wide variety of languages, including SAS, R, HUGIN, and C++.
Ph.D., North Carolina State University, Statistics, 2005
M.A., North Carolina State University, Statistics, 2003
B.S., Towson University, Applied Mathematics and Computing, 2001
Selected Publications and Presentations
Aebischer, D, et al., (2017) Bayesian Networks for Combat Equipment Diagnostics Interfaces, 2017 47:1, p 85-105.
Hepler, A., Saunders, C., Davis, L., and Buscaglia, J. (2012) Score-based likelihood ratios for handwriting evidence Forensic Science International, 219 (1-3), p 129-140.
Dawid, A. P., Hepler, A., and Schum, D. (2011) Inference networks: Bayes and Wigmore. In Evidence, Inference and Enquiry (Proceedings of the British Academy, 171), edited by A. P. Dawid, W. L. Twining and D. Vasilaki, Chapter 5. Oxford University Press, p 119-150.
Hepler, A. and Weir, B. (2008) Object-oriented Bayesian networks for paternity cases with allelic dependencies, Forensic Science International: Genetics, 2, p 166 - 175.
Hepler, A., Dawid, A. P. and Leucari, V. (2007) Object-oriented graphical representations of complex patterns of evidence, Law, Probability and Risk, 6, p 275 - 293.
Weir, B., Anderson, A. and Hepler, A. (2006) Genetic relatedness analysis: modern data and new challenges. Nature Reviews Genetics, Vol. 7, p 771 - 780.