Dr. Zachary K. Collier is an Assistant Professor in the Research Methods, Measurement, and Evaluation program at the University of Connecticut. He is also the director of the newly established Methods for Unstructured and Difficult to use Data (MUDD) Lab. Collier’s major research initiatives are:

1. Developing and applying machine learning and statistics to data in education and social policy

2. Bridging scientific disciplines to combine analytical tools to tackle problems that cross traditional boundaries

Dr. Haobai Zhang graduated in 2018 with her PhD. She's now a Research Scientist at Mathematica exploring large scale datasets to understand the development of mathematical cognition in children and using machine learning to detect the early predictors of later math achievement. 

Olushola Soyoye is a fourth-year PhD student in the MUDD Lab. He is a native of Ogun State, but was born and raised in Lagos, Nigeria. He earned both his bachelor's and master's degrees in mathematics education after studying at Tai Solarin University of Education, Ijebu-Ode and the University of Illinois, Urbana-Champaign. His hobbies are singing, surfing the internet, and reading. His research addresses an important practical issue in propensity score analysis, in which the baseline covariates and the outcome have missing values.

Joshua Sukumar is a fourth-year Ph.D. student from Atlanta, GA. He holds a B.S. in Chemistry & M.S. in Applied Statistics from Kennesaw State University and served as an instructor of statistics there. In his free time, he enjoys cooking and watching Formula 1 racing. His research focuses on using data science at the applied and methodological level to advance analytical methods for social science data. During the summer of 2024, he was a Data Science Intern for NASA at the Goddard Space Flight Center.