Joyee Ghosh

Joyee Ghosh
Associate Professor, Department of Statistics and Actuarial Science, University of Iowa

Educational Background
PhD, Statistics, Duke University
MS, Statistics, Duke University
BSc, Statistics, St. Xavier’s College, Kolkata, India

Joyee Ghosh was born and raised in Kolkata, India. She chose the science track in high school, so mathematics, physics, and chemistry were required subjects. She had an option to choose between statistics and biology and selected statistics mainly to avoid biology labs because the thought of dissecting frogs (or anything else) terrified her. She enjoyed her statistics classes, but her first love was chemistry.

Through a turn of events, Ghosh ended up majoring in statistics and did well in her classes. Her father, who was a renowned statistician, strongly encouraged her to earn a PhD, so she applied to a few schools and decided to go to Duke University, where she had her first exposure to research and computational statistics. Ghosh found that developing a new method/algorithm was exciting. It was a rewarding experience when the method was successful, often after much hard work to overcome challenges.

While she was a graduate student, Ghosh did an internship in a pharmaceutical company and realized she enjoys academic freedom. However, she was unsure about a career in academics. She was fortunate to have supportive family, friends, and academic mentors (at Duke and UNC Chapel Hill, where she did a postdoctoral fellowship), who encouraged her to pursue a career in academics that she truly enjoys today.

Ghosh is an applied Bayesian statistician. The focus of much of her research has been on developing algorithms for Bayesian variable selection. She has also worked on choice of prior distributions, a critical component for Bayesian analysis when there is limited information about some parameters. Her work has been funded by the National Security Agency and National Science Foundation. One of her papers on choice of prior distributions for variable selection under collinearity, co-authored with a former graduate student, was selected as a featured article for an ASA Bayesian statistics campaign and given 90 days of free access.

Currently, Ghosh is advising a graduate student for her dissertation on predicting environmental phenomena using Bayesian variable selection methods. She is also serving as the director of graduate studies for this academic year. When students ask for advice about career paths, she tells them they should follow their heart, work hard, and take things as they come.