Faculty Spotlight: Marcia Pescador Jimenez, PhD, MS, MS

Dr. Marcia Pescador Jimenez is an Assistant Professor of Epidemiology at Boston University School of Public Health. Dr. Jimenez received her PhD in epidemiology from the Brown University School of Public Health and completed an NHLBI T32 postdoctoral fellowship in cardiovascular disease and environmental epidemiology at the Harvard T.H. Chan School of Public Health. Her early work evaluated the relationship between greenspace and hypertension among adults. More recently, she has extended this to examine the relationship between greenspace and cognitive development among children and mediation analysis between greenspace and cognitive function. Her current work focuses on novel metrics of greenspace and the urban environment using Deep Learning Algorithms and Google Street View images. Keep reading to learn more about Marcia and her work!

Tell us about your academic and research background, and how it led you to where you are now.

I was born and raised in Mexico City. I was very interested in mathematics since college, so I went to Belgium to study a Master in Statistics. After that, I knew I wanted to apply this type of methodology to population studies. I discovered epidemiology as a master’s student and found my happy place in academia.

Can you tell us about some of your current research projects?

I am working on environmental determinants of cognitive health and how can we intervene on these exposures to help reduce racial and ethnic disparities in Alzheimer’s Disease and related dementias.

What is the role of data science in your work?

During my postdoc at Harvard, I applied Deep Learning algorithms to Google Street View (GSV) imagery to create novel metrics of green space as participants experience it. As a junior faculty, my team and I are examining racial and ethnic disparities in exposure to GSV-based greenspace. We are also examining associations between GSV greenspace with cognitive decline, dementia risk, and mortality in a racially diverse cohort.

What do you see as the future of data science in your research areas?

Future work involves examining multiple environmental exposures in association with cognitive health. To do this, I would need to use data reduction techniques that can deal with high correlations among environmental exposures at a nationwide level.

What advice would you give to students and trainees interested in this field?

Send that email to your favorite professor to ask about research opportunities. And also, take more walks outside. When I go for a walk and see the trees around me, I can almost immediately feel the stress decrease. This type of work is important, and you can experience some of the benefits from exposure to green space in real time.

What is something about you that others would be surprised to learn?

I eat a piece of dark chocolate every day.