Tom M. Mitchell Research Group

Carnegie Mellon University

How can machine learning decode human brain activity to reveal the neural representations of language meaning during reading? The group uses functional Magnetic Resonance Imaging to capture three-dimensional images of human brain activity and trains machine learning algorithms to decode mental states from those images. The group develops temporal models and classifiers for extremely high-dimensional, noisy fMRI data to discover spatial-temporal activity patterns associated with cognitive tasks. The group builds intelligent workstation assistants that learn from users' email, calendar and text files, focusing on automatic information extraction and cumulative long-term learning. The group applies large language models and student-knowledge tracing to improve online education systems and to select effective teaching actions.