
2024 Fellow
Matt Raymond
Department of Electrical Engineering and Computer Science
Matt Raymond is a Ph.D. candidate in the Department of Electrical Engineering and Computer Science. He is co-advised by Dr. Angela Violi and Dr. Clayton Scott. His research has focused on applied machine learning (ML) for nanochemistry. This includes supervised multitask feature selection using ensemble models for nanochemistry datasets, ML for plasma physics, and transfer learning for predicting protein-nanoparticle interactions. His secondary research had included the graph analysis of combustion networks and bacterial cross-feeding interactions in the human gut, and using natural language processing to perform metascientific analysis of UMich's Mechanical Engineering research output.
The Beyster Fellowship will allow Matt to focus on his main research interest: generative modeling for nanochemistry. Generative modeling has shown much promise in data-rich settings such as natural language processing, protein folding, and molecule design. The automatic design of nanomedicines could revolutionize the treatment of cancers and antibiotic resistant bacteria; however, there is very little nanoparticle data, which makes nanoparticle generation especially difficult. Matt's ongoing research focuses on developing novel generative algorithms for data-poor settings such as medicinal nanochemistry.
Matt organized the Student Signal Processing in EECS (SPEECS) Seminar in the 2023-2024 school year, was a participant in the mentoring program for new Computer Science masters students, and is an active participant in the BuddEEs mentoring program for new Electrical Engineering PhD students.