Michael Burkhart earned his Ph.D. in 2019 from Brown University's Division of Applied Mathematics. He and his advisor, Matthew Harrison, collaborated with the BrainGate clinical trial that develops intracortical brain–computer interfaces to enable persons with quadriplegia to communicate and interact with their environments using mental imagery alone. Together with Leigh Hochberg and David Brandman, they derived and implemented a novel Bayesian filtering framework to predict a participant’s latent intention given all currently available measurements from chronically implanted microarrays. After completing his doctorate, Michael spent three years working as a machine learning scientist at Adobe in California.

Michael recently joined the Adaptive Brain Lab at the University of Cambridge as a research associate to develop machine learning-based approaches for the early diagnosis of neurodegenerative disease, specifically Alzheimer's. He's excited to continue working at the interface of artificial intelligence and neuroscience.