Mathew Rynes


Graduate Student

MS - Biomedical Engineering

University of Minnesota

BS - Neuroscience, Biochemistry

University of Minnesota


Matt received his Bachelor’s degree in Neuroscience and Biochemistry from the University of Minnesota. In his undergraduate research, he worked on applying machine learning algorithms to predict movements from offline monkey dorsal-lateral prefrontal cortex local field potentials. After graduation, he helped develop a lyoprotectant matrix for non-cryogenic storage of human serum at the University of Minnesota mechanical engineering department. Following his work on this project, he continued his studies in the biomedical engineering department. Matt is working on applying highly developed machining tools to perform automated surgical procedures on small animals for neuroscientists.



Ghanbari L, Carter R E, Rynes M, Dominguez J, Chen G, Naik A, Hu J, Abdul S, Haltom L, Mossazghi N, Gray M, West S, Eliceiri K, Ebner T J, Kodandaramaiah S B, Cortex-Wide Neural Interfacing via Transparent Polymer Skulls, BioRxiv

Ghanbari L *, Rynes M*, Hu J, Schulman D S, Johnson G, Laroque M, Shull G, Kodandaramaiah S B, Craniobot: A computer numerical controlled robot for cranial
microsurgeries, Scientific Reports, 2019
Solivio M J, Less R, Rynes M, Kramer M, Aksan A, Adsorbing/dissolving Lyoprotectant Matrix Technology for Non-cryogenic Storage of Archival Human Sera,  Scientific Reports, 6, 24186.
Rynes M*, Vattendahl Vidal G W*, Kelliher Z, Goodwin S J, 2016 Review of Brain-Machine Interfaces Used in Neural Prosthetics with New Perspective on Somatosensory Feedback through Method of Signal Breakdown. Scientifica, vol. 2016, 8956432 *Equal contribution


University of Minnesota Distinguished MS Thesis Award 2018