Marzyeh Ghassemi
  • Visiting Researcher, Verily/Google

    Assistant Professor in Computer Science and Medicine, University of Toronto

    Faculty Member, Vector Institute

    Website | Google Scholar

Research Interests

  • Health
  • Fairness
  • Representation Learning
  • Unsupervised Learning
  • Latent Variable Models
  • Neural Networks
  • Creating and applying machine learning algorithms towards improved prediction and stratification of relevant human risks

Biography

Marzyeh completed her PhD at MIT where her research focused on machine learning in health care, exploring how to predict immediate and long-term patient needs to inform decisions in the intensive care unit and ambulatory care. Her current research interests include clinical risk prediction with semi-supervised learning, optimal treatment discovery using expert demonstrations, and non-invasive patient phenotyping for behavioral conditions. Prior to MIT, she received a B.S. degree in computer science and electrical engineering at New Mexico State University and Master’s degree in biomedical engineering from Oxford University. Marzyeh is on the Board of Women in Machine Learning (WiML), and co-organized the NIPS 2016/2017 Workshop on Machine Learning for Health, and MIT’s first Hacking Discrimination event.

Highlights

  • Nominated for 2017 Best Student Paper at AMIA Summit on Clinical Research Informatics (CRI) for “Predicting Intervention Onset in the ICU with Switching State Space Models”
  • First Place at 2014 MIT $100K Accelerate $10,000 Daniel M. Lewin Accelerate Prize, Kohana Student Team
  • First Place at 2013 MIT Sloan-ILP Innovators Showcase, Sana AudioPulse Student Team
  • American Marshall Scholar 2008

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