My name is William Cipolli III, Will for short. I'm originally from a small town in Connecticut, right outside of New Haven - which I love. Not far from there, I earned my BA in Mathematics and my BS in Computer Science from Quinnipiac University, in Hamden, Connecticut. I completed my PhD in Statistics at The University of South Carolina, in Columbia, South Carolina. Now, I am an assistant professor of mathematics at Colgate University in Hamilton, New York.
Like a lot of students, I chose to study math because it felt like it came naturally to me. I was good at it and, conveniently, the career opportunities are abundant. Of course, mathematics in college and graduate school is painstakingly different than high school. I became well-practiced in failed attempts, patient questioning, and reworking of solutions. My best teachers in college and graduate school guided me past imitative mathematics to curious persistence and intellectual humility in both our questions and our answers. Learning this style of thinking was important because we're all susceptible to missteps and many times a careful, long approach to our work is shorter than sprinting between ill-considered solutions. The effects of taking this approach have touched every part of my life.
As excited as I am about Math and Statistics I do have some other hobbies. I very much enjoy traveling with my partner, cooking and listening to music. For exercise, I enjoy playing squash and chasing our pet Greyhound Dempsey around. I also have and tinker with a 1987 BMW appropriately named Emmy after the German mathematician known for being a bit high maintenance.
Currently, I am an Assistant Professor of Mathematics at Colgate University. I have spearheaded the effort to develop and revise the statistics curriculum at Colgate by designing several courses. These courses include examples, ideas, and theory that come from the intimate connection between my statistics research and engagement with practical problems. My methodological research focuses on Bayesian nonparametric approaches to a variety of problems including multiple testing, density estimation, and supervised learning. This work has been published in journals like Statistics and Computing, and Computational Statistics and Data Analysis. I also collaborate on multidisciplinary projects which have been published in top journals of statistics, sociology, psychology, biology, and medicine.
Please download a copy of my CV, teaching dossier, and research dossier. Also, for those interested, here is my teaching dossier from University of South Carolina, pre-academia resume and here are my Myers-Briggs and Team Dimensions personality profiles.