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Marzyeh Ghassemi

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Marzyeh Ghassemi
EducationNew Mexico State University
University of Oxford
MIT
Scientific career
InstitutionsUniversity of Toronto
MIT
Doctoral advisorPeter Szolovits
Websitehealthyml.org/marzyeh/

Marzyeh Ghassemi is currently a professor at MIT, leading the Healthy ML lab which develops robust machine-learning algorithms, and works to understand how such models can best inform and improve health-care decisions. She was formerly an assistant professor at the University of Toronto's Department of Computer Science and Faculty of Medicine, holding a Canada CIFAR Artificial Intelligence (AI) chair and Canada Research Chair (Tier Two) in machine learning for health.

Research career

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Ghassemi pursued a bachelors of science degree in computer science and electrical engineering at New Mexico State University, a master's degree in biomedical engineering from Oxford University, and a PhD at the Massachusetts Institute of Technology (MIT).[1][2][3]

During her PhD, Ghassemi collaborated with doctors based within Beth Israel Deaconess Medical Center's intensive care unit and noted the extensive amount of clinical data available.[3][4] She then developed machine-learning algorithms to take in diverse clinical inputs and predict risks and mortality, such as the length of the patient's stay within the hospital, and whether additional interventions (such as blood transfusions) are necessary.[2][4][5][6][7] In 2012, Ghassemi was a member of the Sana AudioPulse team, who won the GSMA Mobile Health Challenge as a result of developing a mobile phone app to screen for hearing impairment remotely.[8] Ghassemi was also the lead PhD student in a study where accelerometer data collected from smart wearable devices to successfully detect differences between patients with muscle tension dysphonia (MTD) and those without MTD.[9] Upon completing her PhD, Ghassemi was affiliated with both Alphabet’s Verily (as a visiting researcher) and at MIT (as a part-time post-doctoral researcher in Peter Szolovits' Computer Science and Artificial Intelligence Lab).[2][10]

Ghassemi joined the University of Toronto in fall 2018, where she was co-appointed to the Department of Computer Science and the University of Toronto's Faculty of Medicine, making her the first joint hire in computational medicine for the university.[2][5][11][12][13] Ghassemi's lab was titled the Machine Learning for Health (ML4H) lab.[14][15] Ghassemi was also a faculty member at the Vector Institute.[1] She held the Canada CIFAR Artificial Intelligence (AI) Chair position.[11][16][17] In June 2019, Ghassemi was appointed a Canada Research Chair (Tier Two) in machine learning for health.[18]

Ghassemi joined MIT in 2021, as a professor in Electrical Engineering and Computer Science, and the Institute for Medical Engineering and Science. Ghassemi was selected for a National Science Foundation CAREER award, and has been cited over 13,000 times with an h-index and i-10 index of 54 and 122 respectively.[19] During her PhD she was named as one of the 35 Innovators Under 35, in the visionaries category, in MIT Technology Review's annual list.[2][3], and prior to her PhD she was awarded the Barry M. Goldwater Scholarship and the Marshall Scholarship.

Selected bibliography

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  • Ethical machine learning in healthcare. Irene Chen, Emma Pierson, Sherri Rose, Shalmali Joshi, Kadija Ferryman, Marzyeh Ghassemi. Annual Review of Biomedical Data Science 4, 123-144.
  • The false hope of current approaches to explainable artificial intelligence in health care. Marzyeh Ghassemi, Luke Oakden-Rayner, Andrew L. Beam. The Lancet Digital Health 3 (11), e745-e750.
  • Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations. Laleh Seyyed-Kalantari, Haoran Zhang, Matthew McDermott, Irene Chen, Marzyeh Ghassemi. Nature Medicine 27 (12), 2176-2182.

References

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  1. ^ a b "Marzyeh Ghassemi". Vector Institute for Artificial Intelligence. Retrieved 2019-04-22.
  2. ^ a b c d e "New U of T researcher named to magazine's 'Innovators under 35' list". University of Toronto News. Retrieved 2019-04-22.
  3. ^ a b c "Marzyeh Ghassemi is using AI to make sense of messy hospital data". MIT Technology Review. Retrieved 2019-04-22.
  4. ^ a b iTMunch (2019-02-08). "Innovators, Entrepreneurs, Pioneers | Best Innovators Under 35". iTMunch. Retrieved 2019-04-22.
  5. ^ a b "Who are the new U of T Vector Institute researchers?". The Varsity. 2017-11-13. Retrieved 2019-04-22.
  6. ^ HealthITAnalytics (2017-08-22). "MIT Uses Deep Learning to Create ICU, EHR Predictive Analytics". HealthITAnalytics. Retrieved 2019-04-22.
  7. ^ "Using machine learning to improve patient care". MIT News. 21 August 2017. Retrieved 2019-04-22.
  8. ^ "Sana AudioPulse wins Mobile Health Challenge". MIT News. 7 August 2012. Retrieved 2019-04-22.
  9. ^ "How machine learning can help with voice disorders". phys.orgs. Retrieved 2019-04-22.
  10. ^ "2018 Innovator Under 35: Marzyeh Ghassemi - MIT Technology Review". MIT Technology Review Events. Retrieved 2019-04-22.
  11. ^ a b "Eight U of T researchers named AI chairs by Canadian Institute for Advanced Research". University of Toronto News. Retrieved 2019-04-22.
  12. ^ "Six U of T researchers join Vector Institute". University of Toronto News. Retrieved 2019-04-22.
  13. ^ "Former Google CEO lauds role of universities in Canada's innovation ecosystem". University of Toronto News. Retrieved 2019-04-22.
  14. ^ "Marzyeh Ghassemi: From MIT and Google to the Department of Medicine". Department of Medicine. 2018-09-10. Retrieved 2019-04-23.
  15. ^ "About ML4H". Machine Learning for Health (ML4H). Retrieved 2019-04-23.
  16. ^ "Bio". CIFAR. Retrieved 2019-04-22.
  17. ^ Research, Canadian Institute for Advanced. "29 researchers named to first cohort of Canada CIFAR Artificial Intelligence Chairs". www.newswire.ca. Retrieved 2019-04-22.
  18. ^ "From AI to immigrant integration: 56 U of T researchers supported by Canada Research Chairs Program". University of Toronto News. Retrieved 2019-07-03.
  19. ^ "Marzyeh Ghassemi - Google Scholar Citations". scholar.google.com. Retrieved 2024-10-11.
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