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Pathways Into Mathematical Oncology
What does a career in Mathematical Oncology look like?
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We spoke with leading researchers from across the country who are combining mathematics, computer science, and biology to push the boundaries of cancer research. In these interviews, they share how they got started, what their day-to-day looks like, and the advice they’d give to students curious about this powerful and emerging field.
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Whether you're into data, medicine, or math modeling — their stories show just how impactful a STEM path can be.
Interview with Dr. Thomas Yankeelov
In this interview, Dr. Thomas Yankeelov, Director of the Center for Computational Oncology at The University of Texas at Austin, shares his work at the intersection of biomedical engineering and medicine. With joint appointments in Biomedical Engineering and the Dell Medical School, Dr. Yankeelov focuses on using advanced imaging and mathematical modeling to predict tumor growth and treatment response, with the goal of personalizing and improving cancer care.
Interview with Dr. Naoru Koizumi
In this interview, Dr. Naoru Koizumi—a professor and associate dean at George Mason University and an expert in biomedical data analytics—discusses the power of mathematical modeling in addressing complex healthcare challenges. She shares her insights on interdisciplinary collaboration, the growing role of AI in healthcare, and the joy of mentoring high school students in biomedical research.
Interview with Professor Yang Kuang
In this interview, Dr. Yang Kuang, a professor at Arizona State University and author of Introduction to Mathematical Oncology, explores the critical role of mathematical models in advancing cancer research. Dr. Kuang discusses how mathematical frameworks are used to predict tumor growth, simulate treatment outcomes, and enhance our understanding of cancer biology.
Interview with Dr. Russell Rockne
In this interview, Dr. Russell Rockne, Director of Mathematical Oncology at City of Hope, talks about how mathematical models and machine learning are transforming cancer research and treatment. He explains how these tools help predict tumor growth and personalize therapies, offering a glimpse into the future of personalized medicine.
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