After spending time at three different undergraduate institutions, starting with ESPOL Polytechnic in his native Ecuador, Nicolas Gonzalez Granda (PhD, ’28) found his way to the SPH with a desire to apply his mathematical education to real world public health problems.
Until the COVID-19 pandemic, Nicolas Gonzalez Granda did not consider public health as a career path. “Living through a pandemic in a country whose public health system was not prepared to face any kind of strain — let alone a large-scale, global health emergency — made me realize I would like to apply my skills in public health to make a positive change,” says Gonzalez Granda.
While majoring in mathematics as an undergraduate, he started exploring applied mathematics such as computational statistics and data science, but wasn’t entirely sure of his trajectory until his desire to apply his skills to real-world problems led him to the field of biostatistics. That field, with its focus on the development and application of statistical and modeling techniques, allowed him to apply his math skills to health-related challenges.
“I feel like it’s an environment where knowledge is shared…Everyone has a very similar, shared goal to contribute as best they can.”
Nicolas Gonzalez Granda
That, in turn, drove Gonzalez Granda to enroll in the SPH doctoral program in biostatistics where he received not one, but two scholarships: the SPH Finnegan-Mosberger Family fellowship and the University of Minnesota DOVE fellowship, which contributed greatly to his ability to reach his career goals. The other key to his success here, he claims, is the community and culture.
“I feel like it’s an environment where knowledge is shared,” says Gonzalez Granda. “I never feel the need to watch my back or protect my research. Everyone has a very similar, shared goal to contribute as best they can.”
Gonzalez Granda’s research in the doctoral program focuses on the development of novel applications of established statistical tools. While his specific public health focus is still being developed, he’s particularly interested in leveraging machine learning, natural language processing, and generative AI to address public health challenges.
As an example, he offers an idea he’s been working on: “Think of the potential to leverage all those doctor’s notes that are stored in a patient’s electronic health records,” Gonzalez Granda says, noting the possibility of transforming these notes into a longitudinal data set of a patient’s health history. “Existing AI tools can be used to parse through doctor’s notes and find a pattern that isn’t as easy for humans to pick up.”
Ultimately, Gonzalez Granda hopes to contribute to positive health outcomes, as he is well aware that behind the numbers, models, and data are real people with real health challenges. That fact was brought home in 2021, when he collaborated with a lab in Ecuador to analyze the impact of COVID-19 on pregnant women. The study found a significant number of women in disadvantaged economic positions struggling with worse health outcomes.
“I can only imagine the economic and psychological distress of being pregnant during a pandemic, but to also contract the disease, to not know how it would impact your fetus,” he pauses. “There was power to what I was doing through just analyzing data that might have real people and real impact attached to it. By doing my work, I could be helping to not only make sure that all of their trials were not in vain, but also help people who might be in a similar situation in the future.”
Gonzalez Granda adds, “The best we can do is be prepared.”
