Leili Shahriyari

Leili Shahriyari is an Associate Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. Her research focuses on developing computational frameworks that integrate machine learning, mathematical modeling, and statistical methods to advance personalized cancer therapies. Key initiatives include:

• Digital Twin Platforms: Creating patient-specific models like My Virtual Cancer to predict treatment responses for breast cancer and rare cancers like uveal melanoma.
• QSP Modeling: Enhancing quantitative systems pharmacology (QSP) approaches to personalize treatments using patient-specific data rather than generic datasets.
• TumorDecon Software: A Python package for deconvolving tumor cell composition, supported by NIH-NCI funding.

Education:

• Ph.D. in Mathematics, Johns Hopkins University (2013)
• M.S.E. in Computer Science, Johns Hopkins University (2012)

Research Themes:

• Computational and Mathematical Biology
• Data-Driven Oncology
• Cancer Microenvironment Modeling

Collaborations: Her work intersects interdisciplinary teams in computational biology, bioinformatics, and clinical oncology to advance translational cancer research.