Rate My Professor Herman Ray

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.