Margaux Delporte has joined the University of Rhode Island’s College of Health Sciences as an assistant professor in the Department of Public Health.
The first-time professor joins URI’s faculty after completing her undergraduate and graduate studies in her native country of Belgium followed by a postdoctoral fellowship at Cornell University.
“I was drawn to URI because of the strength of the Department of Public Health’s undergraduate program, the recent addition of the master’s degree in public health program, and URI’s plans to establish a medical school,” said Delporte. “I was excited by the opportunity to contribute to building something new.”
“We are very excited to have Dr. Delporte join our department,” said Professor Molly Greaney, chair of the Department of Public Health. “She has a wealth of expertise in biostatistics and the analysis of longitudinal multivariate data that will benefit our master’s in public health students and undergraduate students, as well as the department and URI.”
Delporte develops and applies statistical methods to address questions in public health. Her research focuses on joint modeling, longitudinal data analysis, high dimensional data, and false discovery rate control.
“URI’s emphasis on applied, collaborative public health research aligns well with my own work, and I was struck by the overlap between my research interests and those of faculty in the Department of Public Health and the Department of Statistics,” said Delporte. “More broadly, my philosophy is to conduct research that makes a difference in people’s lives, and that resonates deeply with URI’s commitment to bettering the health of Rhode Islanders.”
According to Delporte, collecting and interpreting reliable data is vital to making a difference in public health.
“Public health is fundamentally a data-driven field,” stated Delporte. “Statistical methods allow us to move beyond description and understand the determinants of health outcomes. Longitudinal methods allow us to study how health changes over time, which is essential for understanding the progression of chronic diseases and the long-term effects of exposures.”
Delporte is currently developing models for longitudinal data and false discovery rate control.
“The challenge of working with a dataset that has many variables is keeping false positives to a minimum,” said Delporte.
The professor is also working on a tool that gathers and synthesizes evidence on nutritional supplements and breast cancer. The tool searches PubMed for relevant literature and uses large language models to extract the findings of each paper. Then, statistical models are used to summarize all available evidence and determine whether there is an overall effect.
In the coming years, Delporte plans to build an independent research program focused on biostatistical methodology, specifically in false discovery rate control and joint modeling approaches for longitudinal data, while collaborating with colleagues across departments on applied projects involving multivariate, high-dimensional, and longitudinal data. In the classroom, Delporte looks forward to contributing to the master’s degree in public health program and continuing to make biostatistics accessible and interesting to students from diverse and non-quantitative backgrounds.