Rate My Professor Herman Ray

Dr. Herman Ray is a Professor of Data Science and Biostatistics at Kennesaw State University, where his expertise intersects with mathematics through his foundational degrees and statistical methodologies. He earned a B.S. in Mathematics and an M.S. in Mathematics from Middle Tennessee State University in 2001 and 2004, respectively, and a Ph.D. in Biostatistics from the University of Louisville School of Public Health and Information Sciences in 2011. Joining Kennesaw State University in 2011, Ray has advanced through key academic and administrative roles. He founded the Center for Statistics and Analytical Research (CSAR), now the Center for Data Science and Analytics (CDSA), which links Ph.D. students in Data Science and Analytics with industry partners. Currently, he directs the Ph.D. Program in Data Science and Analytics and serves as Associate Dean for Graduate Student Success. Before academia, Ray worked with real-world data since 2000, starting as a Statistician at CIGNA, advancing to a research position at Thomson Reuters, and later as Director of Program Management and Senior Director of Biostatistics and Programming at ConcertAI.

Ray's research centers on methodology development for imbalanced data and the intersection of healthcare and data science, including causal models and incorporating observational data into clinical trials to improve drug and device development processes. He has led funded projects as Principal Investigator for the BlueCross BlueShield of Tennessee Data Science Research Lab and the WellStar Health System Data Science Research Lab, and as Co-Principal Investigator on an NSF grant. His publications, cited over 900 times on Google Scholar, include "Improving logistic regression on the imbalanced data by a novel penalized log-likelihood function" (Journal of Applied Statistics, 2021, with L. Zhang et al.), "Perceived stress, work-related burnout, and working from home before and during COVID-19" (Sage Open, 2021, with S.W. Hayes et al.), "A descriptive study of variable discretization and cost-sensitive logistic regression on imbalanced credit data" (Journal of Applied Statistics, 2020), "Predictors of mortality and outcomes of acute severe cardiogenic shock treated with the Impella device" (American Journal of Cardiology, 2019, with C.L. Rohm et al.), and "Finding the Proverbial Needle: Improving Minority Class Identification Under Extreme Class Imbalance" (Journal of Classification, 2022). These works advance biostatistics, machine learning, healthcare analytics, and education policy.