Haley Grant

Contributions to Public Health

• Teaching and Mentoring: Education is the primary focus of my work at Pitt. I teach statistics through the lens of public health research and practice, offering foundational biostatistics courses such as Introduction to Statistical Methods, Biostatistical Methods, and Applied Regression Analysis to train the next generation of public health researchers and practitioners. Through my classes, I strive to prepare students for public health careers by providing an intuitive, applications-based understanding of fundamental statistical methods.
• Statistical Analysis of Electronic Health Record (EHR) data: I collaborate with the PaTH network working on projects leveraging EHR data to study health conditions and care patterns. I also contribute to a working group focused on evaluating and improving EHR data quality to support meaningful and generalizable research across diverse populations and health outcomes.
  • Bober, T., Cameron, F., Alexander, L., Luiggi-Hernandez, J. G., Rometo, D., Lavenburg, L.-M., Grant, H., Klawson, E., Boyer, A. R., McTigue, K. M., Gouveia-Pisano, J., Patel, A., Tarasenko, L., Escobar, J., Brenner, A., Vouri, S. M., Dai, F., & Hamm, M. E. (2025). Characterizing obesity: A qualitative study. Obesity Pillars, 14, 100174.
  • Lavenburg, L. M., Gao, Y., Grant, H., Rometo, D., Bober, T., Boyer, A., Bradley, A., Cappella, N., Hamm, M., Gouveia-Pisano, J., Vouri, S. M., Tarasenko, L., Dai, F., & McTigue, K. (2024, November). Characterizing obesity and the use of available treatments in a large academic health system. Obesity (Silver Spring), 32, 94.
• Cancer Early Detection: A major component of my doctoral research focused on developing statistical and machine learning models for non-invasive cancer detection using blood-based biomarkers derived from circulating cell-free DNA.
  • Douville, C., Lahouel, K., Kuo, A., Grant, H., Avigdor, B. E., Curtis, S. D., Summers, M., Cohen, J. D., Wang, Y., Mattox, A., Dudley, J., Dobbyn, L., Popoli, M., Ptak, J., Nehme, N., Silliman, N., Blair, C., Romans, K., Thoburn, C., … Tomasetti, C. (2024). Machine learning to detect the Sines of cancer. Science Translational Medicine, 16(731).
  • Lahouel, K., Douville, C., Diergaarde, B., Cohen, J. D., Grant, H., Kuo, A., Ansari, S. K., Wang, Y., O’Broin-Lennon, A. M., Popoli, M., Ptak, J., Silliman, N., Dobbyn, L., Nehme, N., Tie, J., Gibbs, P., Papadopoulos, N., Kinzler, K. W., Vogelstein, B., Schoen, R. E., & Tomasetti, C. (2025). A blood-based assay for detection of patients with advanced adenomas. Cancer Research Communications, 5(4), 621–631.
• Biostatistical Collaboration: I serve as a statistical consultant for the Biostatistics, Epidemiology, and Research Design (BERD) core of the Clinical and Translational Science Institute (CTSI), supporting the design and analysis of clinical and translational research across the University of Pittsburgh.