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  • Colloquium on Digital Transformation Science
  • September 24, 3 pm CT

    Towards AI for Healthcare with Applications to the COVID-19 Pandemic

    Sanmi Koyejo, Assistant Professor of Computer Science, University of Illinois at Urbana-Champaign


    With the emergence of public healthcare crises such as the COVID-19 Pandemic, it is increasingly evident that AI is among the most powerful tools for addressing early detection of diseases, triage, treatment planning, and patient management, among many other pressing healthcare problems. What will it take to build effective machine learning systems for healthcare? This talk will outline our research progress towards answering this question. To this end, I will present emerging technical advances in federated learning, modeling, evaluation, privacy, and trustworthiness. I will also outline how we are bringing these tools to bear to aid in analyzing medical images from COVID-19 patients.

    Sanmi Koyejo is an Assistant 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 adaptive and robust machine learning. Additionally, Koyejo focuses on applications to neuroscience and biomedical imaging. Koyejo has been the recipient of several awards including a Best Paper award from the Conference on Uncertainty in Artificial Intelligence (UAI), a Kavli Fellowship, an IJCAI Early Career Spotlight, and a trainee award from the Organization for Human Brain Mapping (OHBM). Koyejo serves on the board of the Black in AI organization.

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