The “Healthy ML” group at MIT, led by Dr. Marzyeh Ghassemi, focuses on creating and applying machine learning to understand and improve health in ways that are robust, private and fair. Health is important, and improvements in health improve lives. However, we still don’t fundamentally understand what it means to be healthy, and the same patient may receive different treatments across different hospitals or clinicians as new evidence is discovered, or individual illness is interpreted.

Unlike many problems in machine learning - games like Go, self-driving cars, object recognition - disease management does not have well-defined rewards that can be used to learn rules. Models must also be “healthy”, in that they should not learn biased rules or recommendations that harm minorities or minoritized populations. The Healthy ML group tackles the many novel technical opportunities for machine learning in health, and works to make important progress with careful application to this domain.

Read more about our Research Directions and Publications.


  • June 2024 - Congratulations to Haoran, whose work was published in Nature Medicine and featured in MIT News!
    • The Limits of Fair Medical Imaging AI in Real-World Generalization [Paper]
      Yuzhe Yang*, Haoran Zhang*, Judy W. Gichoya, Dina Katabi, Marzyeh Ghassemi
  • May 2024 - Congratulations to Kimia, Haoran, and Swami, who presented their paper at ICLR 2024 as a spotlight!
    • Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation [Paper]
      Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan, Marzyeh Ghassemi

Joining the Lab

As an MIT undergrad interested in an UROP: Contact Katie O’Reilly (oreilly1@mit.edu) to determine if there are research slots available for the semester, and schedule a 30 minute session with Dr. Ghassemi.

As an MIT MEng: Contact Katie O’Reilly (oreilly1@mit.edu) with a topic and research plan that is relevant to the group.

As an external student: Apply for the MIT EECS or IMES PhD programs, select Marzyeh Ghassemi as a PI you are interested in working with.