The Math department at Bryant is a vibrant community of researchers and collaborators--students and faculty alike. Here are some recent and on-going projects!
Several faculty members and students are collaborating on a project funded by a joint grant from the CAS and SAO to create new machine learning techniques for analyzing accident data. One goal is to create a model that can predict the cost associated with car accidents based on images of the damaged vehicles.
Jonathan Huntley '21, 3rd Place Analytics Without Borders, “Under Pressure: A Case Study of the Effects of External Pressure on MLB Players using Twitter Sentiment Analysis”
Kaitlyn Fales '21, 3rd Place Analytics Without Borders, “Instrumental vs. Expressive: A Study of Voter Behavior Models Through the Lens of Identity in the 2016 Presidential Election"
Matthew Bonas '19, 5th Place Northeast Decision Sciences Institute Conference, "Predicting Vehicle Damage Using Machine Learning Techniques"
Edward Golas '20: Nguyen, S., Golas, E., Zywiak, W., & Kennedy, K. (2019). "Dimension Reduction in Bankruptcy Prediction: A Case Study of North American Companies. In Advances in Business and Management Forecasting." Emerald Publishing Limited. https://doi.org/10.1108/S1477-407020190000013010
Anthony Park '19: Nguyen, S., & Park, A. (2020). "A Comparison of Machine Learning Algorithms of Big Data for Time Series Forecasting Using Python." In Segall, R. S., & Niu, G. (Ed.), Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities (pp. 197-218). IGI Global. https://www.igiglobal.com/chapter/a-comparison-of-machine-learning-algorithms-of-big-datafortime-series-forecasting-using-python/248878
Matthew Bonas '19: Bonas, M., Nguyen, S., Olinsky, A, & Quinn, J. (2020). “A Method to Determine the Size of the Resampled Data in Imbalanced Classification”. Contemporary Perspectives on Data Mining, Volume 4. https://www.infoagepub.com/products/Contemporary-Perspectives-in-Data-Mining-Vol-4
Jonathan Ormsbee '18: Nguyen, S., Niu, G., Quinn, J., Olinsky, A., Ormsbee, J., Smith, R. M., & Bishop, J. (2019). "Detecting Non-injured Passengers and Drivers in Car Accidents: A New Under-resampling Method for Imbalanced Classification." In Advances in Business and Management Forecasting. Emerald Publishing Limited. https://doi.org/10.1108/S1477-407020190000013011