Algorithmic Fairness and Transfer Learning in Healthcare Data

Lecture / Panel
For NYU Community

Image depicting data chip


Rumi Chunara, PhD
Associate Professor, Department of Computer Science and Engineering
NYU Tandon
Department of Biostatistics at NYU School of Global Public Health


Until now, much of the work on machine learning and health has focused on processes inside the hospital or clinic. However, this represents only a narrow set of tasks and challenges related to health; there is greater potential for impact by leveraging machine learning in health tasks more broadly. In this presentation Dr. Chunara aims to highlight potential opportunities and challenges for machine learning within a holistic view of health and its influences. To do so, she builds on research in population and public health that focuses on the mechanisms between different cultural, social and environmental factors and their effect on the health of individuals and communities. She will present a brief introduction to research in these fields, data sources and types of tasks, and use these to identify settings where machine learning is relevant and can contribute to new knowledge. Given the key foci of health equity and disparities within public and population health, she juxtaposes these topics with the machine learning subfield of algorithmic fairness to highlight specific opportunities where machine learning, public and population health may synergize to achieve health equity.

Dr. Chunara got her BS degree in Electrical Engineering (EE) from the California Institute of Technology. Subsequently, she moved to the Massachusetts Institute of Technology where received an MS degree in EE, before going on to complete a PhD degree in Medical and Electrical Engineering at the Harvard–MIT Program in Health Sciences and Technology. After spending time as a postdoctoral fellow and instructor at the Harvard Medical School and Boston Children's Hospital, Dr. Chunara joined the faculty at NYU Tandon in 2015. In 2018, she received a coveted Bill & Melinda Gates Foundation Grand Challenges Award to improve vaccination rates in Pakistan through smart immunization targeting. Other major honors include an NSF CAREER Award (2019) and a Sabbatical Award from the German Max Planck Society (2021).


Example of fine-scale ozone measures calculated to be appropriate for health
Example of fine-scale ozone measures calculated to be appropriate for health surveillance at the census tract level for all US census tracts in (a) Chesapeake, VA, and (b) Downey, CA (in 2021).