Tanzy Love

Tanzy Love, PhD is an Associate Professor in the Department of Biostatistics and Computational Biology at the University of Rochester. She holds a PhD from Iowa State University (2005) and specializes in advanced statistical methodologies with applications in environmental health, genomics, and public health. Her research focuses on clustering algorithms, Bayesian models, and machine learning for complex data analysis.

Education: Ph.D. in Biostatistics from Iowa State University (2005).

Research Interests: Environmental health statistics, latent variable models, mixed regression, Bayesian ensemble learning, network data analysis, and applications in virology and neurodevelopmental studies. She has contributed to projects involving HIV-1 infection modeling, mercury exposure impacts on child development, and agricultural water safety using machine learning techniques.

Her recent work emphasizes scalable statistical methods for large datasets, including spatial network models and ensemble learners. She collaborates on studies involving microbial source tracking, food safety, and public health epidemiology.

Key contributions include the HIITE algorithm for HIV infection timing and the SPMM framework for multi-variant infection analysis. Her research has been funded through NIH grants and applied to global health challenges like mercury toxicity and pandemic-related healthcare trends.