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.
Faculty Member
Assistant Professor (Status Only.), Department of Computer Science, Faculty of Arts & Science, University of Toronto
Canada CIFAR Artificial Intelligence Chair
Assistant Professor in Computer Science and Medicine, University of Toronto
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
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
Publications
Ethical machine learning in healthcare
2021
The false hope of current approaches to explainable artificial intelligence in health care
2021
An empirical framework for domain generalization in clinical settings
2021
Implementing machine learning in medicine
2021
The role of machine learning in clinical research: transforming the future of evidence generation
2021
Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations
2021
A quality assessment tool for artificial intelligence-centered diagnostic test accuracy studies: QUADAS-AI
2019
Probabilistic machine learning for healthcare
2021
Problems in the deployment of machine-learned models in health care
2024
A comprehensive EHR timeseries pre-training benchmark
2021
Characterizing generalization under out-of-distribution shifts in deep metric learning
2021
In medicine, how do we machine learn anything real?
2022
Learning Optimal Predictive Checklists
2021
Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning
2019
Outcomes in patients with and without disability admitted to hospital with COVID-19: a retrospective cohort study
2022
Automatic localization and brand detection of cervical spine hardware on radiographs using weakly supervised machine learning
2022
An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study
2021
Medical Dead-ends and Learning to Identify High-risk States and Treatments
2021
Understanding the Variance Collapse of SVGD in High Dimensions
2021
Dear watch, should I get a COVID test? designing deployable machine learning for wearables
2021
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum
2022
Problems associated with the deployment of machine learning-based models in health
2021
Implementing machine learning in healthcare
2021
Problèmes associés au déploiement des modèles fondés sur l’apprentissage machine en santé
2021
Mise en œuvre de l’apprentissage machine en santé
2021
Improving Mutual Information Estimation with Annealed and Energy-Based Bounds
2021
Caractéristiques et issues des hospitalisations pour les cas de COVID-19 et d’influenza dans la région de Toronto
2021