Rate My Professor Mohammad Sahtout

Mohammad Sahtout holds a Ph.D. in Statistics from Kansas State University, obtained in 2014. His doctoral dissertation, titled 'Improving the Performance of the PAM Algorithm via Different Thresholding Methods and Heteroscedastic Modeling,' advanced the Prediction Analysis of Microarrays (PAM) method for high-dimensional gene expression data classification in cancer studies. Sahtout extended the algorithm with hard and order thresholding techniques and introduced heteroscedastic modeling, resulting in superior parameter estimates, higher prediction accuracy, and more parsimonious models when evaluated on 10 multi-class human cancer microarray datasets. Earlier, he completed a master’s degree report in 2009 on 'Type I Error Rates Under Covariance Model Selection in Mixed Linear Models,' analyzing AIC performance for covariance structures like ARMA(1,1), AR(1), and MA(1) using balanced repeated measures data and SAS Proc Mixed. His master’s thesis from 2005-2006, 'On Sup-Entropy Measures,' generalized sup-entropy to other entropy measures, derived relationships, computed values for geometric and exponential distributions, and applied them to the normal approximation of the binomial distribution using Mathematica.

Sahtout's career includes roles in applied statistics and biostatistics. Following his Ph.D., he worked as a Statistics Specialist in the Statistics and Analysis Division, Development Sector, United Arab Emirates, where he designed multi-stage sampling for disease surveillance studies on Foot-and-Mouth disease and Brucellosis, and conducted shelf-life analyses for yogurt using mixed linear models and survival analysis in SPSS. From September 2019 to February 2021, he served as Senior Statistician at the University of California, Davis. Subsequently, he contributed to biopharmaceutical research at AbbVie, co-authoring papers such as 'Efficacy and Safety of Dilpacimab (ABT-165) versus Bevacizumab in Previously Treated Metastatic Renal Cell Carcinoma: Results from a Randomized Phase 2 Trial' (Future Oncology, 2022), phase 1 dose-escalation studies with livmoniplimab (2024), and combination therapy abstracts for advanced solid tumors. Currently, he is Associate Director of Biostatistics at Scholar Rock. Key publications include 'A Nonparametric Lack-of-Fit Test of Constant Regression in the Presence of Heteroscedastic Variances' (Symmetry, 2021, with Gharaibeh, Wang, and Wang), featuring a k-nearest neighbor-based test with asymptotic distribution and strong simulation performance. He received conference travel awards in 2013, the Glen Yoquelet Scholarship in 2009, and serves as UAE Kansas State University Alumni Ambassador since 2015. His research spans nonparametric tests, Bayesian sample size calculations, and statistical consulting.