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Paul K. Newton is a prominent researcher in the field of Computational Oncology, focusing on the intersection of mathematical modeling and cancer research. He leads the Computational Oncology Lab at the University of Southern California. His work involves employing advanced mathematical methodologies to understand cancer dynamics and develop innovative therapeutic strategies. Newton has contributed significantly to the field, evidenced by his publications and participation in major conferences such as the AACR Annual Meeting. In 2020, he was elected as a Fellow of the American Association for the Advancement of Science, reflecting his esteemed standing in the scientific community. Additionally, he collaborates with a diverse group of researchers and students, contributing to the academic growth of emerging scholars in mathematical biology. Newton's research interests include modeling cancer evolutionary dynamics, machine learning applications in oncology, and dynamic games in biological systems.
University of Southern California • Los Angeles, CA
Engaged in teaching and research in the field of Computational Oncology, mentoring graduate students, and leading the Computational Oncology Lab.
GRE is NOT required for Master's applicants for 2025-2026.