Rate My Professor Rachael Blair

Blair's research interests encompass mathematical biology, optimization, numerical analysis, inverse problems, statistics, scientific computing, network analysis, systems biology, community and module detection in high-throughput data, differential equations, mathematical modeling, and graphical models, with applications to high-dimensional omics data integration, metabolic and genetic networks, cancer metabolism, and social systems. She has secured funding such as a National Science Foundation grant for developing mathematical models of skin and breast cancer metabolism using probabilistic graphical models. Key publications include "Integrated regulatory and metabolic networks of the tumor microenvironment for therapeutic target prioritization" (2023, Statistical Applications in Genetics and Molecular Biology), "Stability estimation for unsupervised clustering: A review" (2022, Wiley Interdisciplinary Reviews: Computational Statistics), "Probabilistic graphical models in modern social network analysis" (2015, Social Network Analysis and Mining), "What can causal networks tell us about metabolic pathways?" (2012, PLoS Computational Biology), and "Bootstrapping estimates of stability for clusters, observations and model selection" (2019, Computational Statistics). Blair has earned the SUNY Chancellor's Award for Excellence in Faculty Service (2024), UB School of Public Health and Health Professions Outstanding Junior Researcher Award (2017), Department of Biostatistics Awards for Teaching Excellence (2012, 2013), and Baypath University Distinguished Teaching Award (2021). She has contributed as an associate editor for Advances in Systems Biology, organized conferences including ASA UPSTAT and UB IAD Days, and served on multiple NSF and NIH review panels, enhancing biostatistics and data science education.