Jason Freels is an Assistant Professor of Systems Engineering in the Department of Systems Engineering and Management. Jason's research interests include advanced data analytics for reliability estimation and prediction on systems of systems, computational statistics, software development, and advancing statistics education through literate programming.
Jason is the deputy director for both the Test Science Research Consortium and the Scientific Test and Analysis Techniques Center of Excellence and is a founding member of the AFIT Data Science Lab.
PhD, Air Force Institute of Technology, 2013
MS, Air Force Institute of Technology, 2006
Materials Science & Engineering
BS, Auburn University, 2000
D. H. Collins, J. K. Freels, A. V. Huzurbazar, R. L. Warr, and B. P. Weaver (2013), “Accelerated Test Methods for Reliability Prediction”, Journal of Quality Technology, 45, No. 3, 244-259.
J. K. Freels, J. J. Pignatiello, R. L. Warr, and R. R. Hill (2013), “Bridging the Gap Between Quantitative and Qualitative Accelerated Life Tests”, Quality and Reliability Engineering International, to appear.
J. K. Freels, J. J. Pignatiello,R. L. Warr, and R. R. Hill (2013), “Maximum Likelihood Estimation for the Poly Weibull Distribution”, Reliability Engineering and System Safety, under review.
H. Kilic, S. R. Soni, R. Patel, and J. K. Freels, “Effect of Z-Fiber Percentage on the Fracture Behavior of DCB Specimens in Mode I,” The 14th International Conference on Computational & Experimental Engineering and Sciences, ICCES'07, 3-8 January, 2007, Miami, FL, USA.
D. H. Collins, J. K. Freels, A. V. Huzurbazar,R. L. Warr, and B. P. Weaver, “Accelerated Test Methods for Reliability Prediction”. Los Alamos National Lab TSC Directorate Science Highlights, 134–135, LA-UR-12-20429 (2012).