Sharmistha Guha is an Assistant Professor (tenure-track) in the Department of Statistics at Texas A&M University. Previously, she was a postdoctoral fellow in the Department of Statistical Science at Duke University. She has earned her Ph.D. in Statistics from the University of California, Santa Cruz in 2019. Her research focus includes development of scalable Bayesian methods for object oriented data, supervised network data, and dimensionality reduction, where she draws motivation broadly from applications in neuroscience. She also develops methods in causal inference where observational data are spread over multiple files. She has been developing models for simultaneous Bayesian inference on probabilistic record linkage and causal effects. She has been a recipient of several awards, including the Leonard J. Savage Award (Honorable Mention) in 2021 for the best Bayesian dissertation for her work on Bayesian regression with networks.