Inna Cohen
Inessa (Inna) Cohen, is a PhD student in Computational Biology and Biomedical Informatics at Yale University. Her research sits at the intersection of epidemiology, machine learning, and natural language processing, where she develops computational methods to improve dementia measurement and early detection from electronic health record data and Medicare claims. She is particularly interested in addressing bias and missingness in real-world healthcare data and building methods that generalize across clinical settings. As part of the Geriatric Emergency Care Applied Research (GEAR) network, she collaborates with clinicians, statisticians, and data scientists to harmonize multi-institutional data for aging research. Inna received her MPH in Chronic Disease Epidemiology and Public Health Modeling from the Yale School of Public Health.
What do you do with Data Science?
I’m excited to help cultivate a collaborative data science community at Yale while advancing research to improve the health and care of older adults.