Isabella (Izzy) Caffarelli, a senior majoring in applied mathematics and minoring in astrophysics, both in Arts & Sciences, is looking forward to a new research challenge after she graduates from WashU. After years of studying black holes, Caffarelli is pivoting to another complex computational task: helping brain scientists use advanced algorithms to sort and understand neurological data in a cleaner, more coherent way. She starts her new postbaccalaureate position with the National Institutes of Health (NIH) in Bethesda, Md., in July.
A Chicago native, Caffarelli began pursuing research during her sophomore year at WashU. Looking to combine her interests in math and astrophysics, she approached Henric Krawczynski, the Wilfred R. and Ann Lee Konneker Distinguished Professor in Physics, for advice.
“He was my professor in a first-year seminar called ‘All About Black Holes,’” Caffarelli said. “That course really got me interested in astrophysics. It was a small class, so he knew me well.” She has continued to work with Krawczynski since 2023.
Caffarelli also worked as an academic mentor for Physics I and Calculus II at WashU’s Learning Center for two semesters. “It was really helpful to learn how to prompt students with questions rather than answering the problems for them,” she said.
In spring 2025, Caffarelli studied abroad at the University of Edinburgh, one of the U.K.’s top-rated research universities. For her last undergraduate summer, she worked for the U.S. Department of Energy Office of Science at Argonne National Laboratory, completing a prestigious Science Undergraduate Laboratory Internship.
Here, Caffarelli describes what she likes best about her analytical work.
Have you always known that you wanted to be a scientist or a mathematician/scientist?
No, I just stuck with what I was good at. (Laughs). As an undergrad, I knew that I didn’t want to do engineering because I wanted to take other classes. I enjoyed women and gender studies classes at WashU. I’ve taken Spanish and other interesting classes about political theory. I’m happy to have pursued many interests as an undergrad.
What do you like most about your current research with black holes?
When you’re in astrophysics, you can take a step back and remove yourself from the bubble of daily life. We don’t know what black holes look like, but it’s cool to think that X-rays give us a representation of what is actually happening based on the data. It’s also cool to think that because the black hole system that we’re studying is so far away, we’re seeing light curves from thousands of years ago — or even millions! That puts everything in perspective.
How will you apply what you have been learning to your new opportunity with the NIH?
The NIH lab I am joining studies functional imaging methods. It’s part of the Laboratory of Brain and Cognition and the National Institute of Mental Health. The researchers are particularly interested in improving functional MRI (fMRI) tools, which are used to track blood flow and map activity in different areas of the brain. Because of the large amount of data involved, the lab sometimes uses the same techniques that Henric and I have been using with astronomical data.
The core of the problem for both of these methodologies has been: There’s so much data, how do we handle all of this? And both have been using different types of neural networks to decompose the data into a representation that’s more readable to scientists. These methods have been helpful in recent years with data extraction and understanding what we’re looking at.
So, for my physics research, that’s the changes in the X-ray fluxes for black holes, where obviously there’s a lot of data coming in from telescopes. But then it’s the same thing for fMRIs. There’s a lot of neurological data that needs to be sorted and understood in a cleaner, more coherent way.
