How can data science and machine learning be used to illuminate and reduce inequality in health care and public health?
The December seminar of the Center for Quantitative Methods and Data Science (QM&DS), in partnership with the Biostatistics, Epidemiology and Research Design (BERD) Center at Tufts CTSI and the Data-Intensive Studies Center (DISC) at Tufts University, is Wednesday, December 15, 2:00-3:30PM via Zoom. The topic is Using Machine Learning to Increase Equality in Health Care and Public Health, presented by Emma Pierson, PhD, MS.
Our society remains profoundly unequal. Worse, there is abundant evidence that algorithms can, improperly applied, exacerbate inequality in health care and other domains. This talk pursues a more optimistic counterpoint – that data science and machine learning can also be used to illuminate and reduce inequality in health care and public health – by presenting vignettes about women’s health, COVID-19, and pain.
Emma Pierson, PhD, MS is an Assistant Professor of computer science at the Jacobs Technion-Cornell Institute at Cornell Tech and the Technion, and a computer science field member at Cornell University. She develops data science and machine learning methods to study inequality and healthcare. Her work has been recognized by a Rhodes Scholarship, Hertz Fellowship, Rising Star in EECS, MIT Technology Review 35 Innovators Under 35, and Forbes 30 Under 30 in Science. She has written for The New York Times, FiveThirtyEight, The Atlantic, The Washington Post, Wired, and various other publications.
Wednesday, December 15, 2:00-3:30PM, via Zoom
To attend, please register here via Tufts CTSI I LEARN.