Alexander Franks

Alexander Franks is an Associate Professor in the Department of Statistics and Applied Probability at the University of California, Santa Barbara. His research spans causal inference, covariance estimation, high-throughput biology, and sports analytics. He holds an NIH R01 grant to study post-transcriptional regulation in single cells, collaborating with Nikolai Slavov at Northeastern University.

• Ph.D. in Statistics, Harvard University, 2015
• Sc.M. in Applied Mathematics, Brown University, 2010
• Sc.B. in Computer Science and Applied Mathematics, Brown University, 2009

Dr. Franks' research focuses on causal inference and sensitivity analysis, particularly methods for assessing sensitivity to untestable assumptions. He develops approaches for causal inference with multiple concurrent treatments and multiple outcomes, exploring how dependencies inform sensitivity analysis. His work on covariance estimation characterizes variability in large-scale covariance matrices across multiple groups and as a function of continuous covariates. In high-throughput biology, he studies the relationship between mRNA and protein levels to understand post-transcriptional regulation. Additionally, he applies statistical methods to sports analytics, particularly basketball, analyzing player-tracking data and performance metrics.

Dr. Franks' recent publications (2021-2025) demonstrate a strong focus on causal inference with multiple treatments and outcomes, sensitivity analysis for unobserved confounding, and covariance estimation. His work bridges theoretical statistics with applications in biology, public policy, and sports. Notable trends include the development of copula-based sensitivity analysis, Bayesian approaches to partial identification, and applications to diverse fields including abortion policy, gun control, neuroscience, and single-cell proteomics.

Dr. Franks currently holds an NIH R01 grant to study post-transcriptional regulation in single cells, collaborating with Nikolai Slavov at Northeastern University. His research group develops statistical methodology with practical applications across multiple domains. His GitHub repositories "mgCov" and "factor-sensitivity" provide open-source implementations of his statistical methods for covariance estimation and sensitivity analysis.

Dr. Franks collaborates with researchers across disciplines, particularly in biology and sports analytics. His work with Nikolai Slavov at Northeastern University focuses on single-cell proteomics. His research integrates statistical methodology development with practical applications in biological and social science domains, contributing to both theoretical advances and real-world problem solving.