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Marzyeh Ghassemi

3 Marzyeh Ghassemi_bw

Appointment

  • CIFAR Azrieli Global Scholar 2020-2022
  • Learning in Machines & Brains

Institution

  • Vector Institute
  • University of Toronto
Departments of Computer Science and Medicine

Country

  • Canada

Education

PhD (Computer Science), Massachusetts Institute of Technology
MSc (Biomedical Engineering), University of Oxford
BSEE/BSCS (Electrical Engineering/Computer Science), New Mexico State University

About

Marzyeh Ghassemi’s research goal is to create novel machine learning approaches that can be used to improve healthcare delivery, understand what it means to be healthy, and quantify the impact of possible interventions.

Many of the most interesting technical questions in machine learning are inspired by real use cases, and the explosion of clinical data provides an exciting new set of challenges. Ghassemi’s work explores the frontiers of causality, time series analysis and representation learning in this effort. The overall goal of her group is to learn “healthy” models of human health.

 

Awards

2008 British Marshall Scholar

2018 MIT TechReview “35 Innovators Under 35”

2018 Canada CIFAR AI Chair

2019 Canada Research Chair in Machine Learning for Health, Natural Sciences and Engineering Research Council (NSERC)

 

Relevant Publications

Clinical Intervention Prediction and Understanding with Deep Neural Networks
H Suresh, N Hunt, A Johnson, LA Celi, P Szolovits, M Ghassemi
Machine Learning for Healthcare Conference, 322-337
Predicting intervention onset in the ICU with switching state space models
M Ghassemi, M Wu, MC Hughes, P Szolovits, F Doshi-Velez
AMIA Summits on Translational Science Proceedings 2017, 82
Can AI Help Reduce Disparities in General Medical and Mental Health Care?
IY Chen, P Szolovits, M Ghassemi
AMA Journal of Ethics 21 (2), 167-179
Practical guidance on artificial intelligence for health-care data
M Ghassemi, T Naumann, P Schulam, AL Beam, IY Chen, R Ranganath
The Lancet Digital Health 1 (4), e157-e159
Semi-Supervised Biomedical Translation with Cycle Wasserstein Regression GANs
MBA McDermott, T Yan, T Naumann, N Hunt, H Suresh, P Szolovits, ...
Thirty-Second AAAI Conference on Artificial Intelligence

 

 

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