Matt鈥檚 research investigates the convergence of craft, design, and emerging AI. He explores how machine learning enhances the creative exploration phase and shapes physical artifacts鈥攆rom algorithmic design tools to interactive, AI-embedded objects that interrogate the human-AI relationship using ethical and open-source frameworks. His work bridges quantitative data science with hands-on practice, redefining the boundaries of contemporary functional design.
Professional Experience
Matt received his Ph.D. in particle physics from Syracuse University in 2018, where his graduate research focused on data analysis of proton-proton collisions at the LHCb experiment on the Large Hadron Collider in Geneva, Switzerland. After graduation, he spent four years as a postdoctoral scholar at Lawrence Berkeley National Laboratory and a postdoctoral fellow at Wayne State University, conducting high-energy nuclear physics research at the STAR experiment on the Relativistic Heavy-Ion Collider. Throughout his research career, Matt explored the use of AI/ML analytical techniques to improve experimental data analysis, leading to several peer-reviewed papers and international conference presentations.
In 2022, he joined Ford Motor Company as a senior data scientist, developing AI/ML models to improve the customer experience for Ford鈥檚 Customer Service Division. Currently, he manages a team of data scientists, as well as software and data engineers, continuing to develop AI/ML solutions for Ford.
Matt is also the co-founder and CEO of Thibodeau Ceramic Design, a ceramic design studio focused on contemporary functional and sculptural ceramics that supports early-career artists and designers through collaborative creative practices. In this role, he explores the intersection between traditional craft, emerging AI technologies, and creative entrepreneurship.
Significant Publications, Presentations and Exhibitions
D. H. Knapp et al., 鈥淪oundtrap during COVID-19: A machine-learning approach to assess the effects of the pandemic on music education鈥�, Research Studies in Music Education, 2023.
M. S. Abdallah et al. (STAR Collaboration), 鈥淓vidence of Mass Ordering of Charm and Bottom Quark Energy Loss in Au+Au Collisions at RHIC鈥� , EPJ C, 2022.
M. Kelsey et al., 鈥淐onstraints on Gluon Distribution Functions in the Nucleon and Nucleus from Open Charm Hadron Production鈥� , Phys. Rev. D, 2021.
M. Kelsey, 鈥淣uclear modification factors, directed and elliptic flow of electrons from open heavy flavor decays in Au+Au collisions from STAR鈥� , Nuclear Physics A, 2021.
R. Aaij et al. (LHCb Collaboration), 鈥淢easurement of the b-hadron fractions in 13 TeV pp collisions鈥�, Phys. Rev. D, 2019.