When will AI read your brain? The Promises and Pitfalls of AI in Brain Imaging


Machine learning and artificial intelligence are exciting tools for the scientific and medical analysis of brain images. Yet, despite years of effort, the human brain remains one of the most fascinating yet least understood complex biological systems. Robust neural biomarkers for most diseases remain unknown, and treatments are often trial-and-error. Understanding brain function is essential and timely, as neurological and neuropsychiatric disorders create an enormous burden on individuals, along with a staggering societal cost.What will it take for AI to revolutionize brain science? This talk will outline some successes, failures, and future opportunities for AI in brain imaging.


Sanmi Koyejo an Associate Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Koyejo's research interests are in developing the principles and practice of trustworthy machine learning. Additionally, Koyejo focuses on applications to neuroscience and healthcare. Koyejo has been the recipient of several awards, including a best paper award from the conference on uncertainty in artificial intelligence (UAI), a Skip Ellis Early Career Award, a Sloan Fellowship, an NSF CAREER award, a Kavli Fellowship, an IJCAI early career spotlight, and a trainee award from the Organization for Human Brain Mapping (OHBM). Koyejo serves as the president of the Black in AI organization.