Professor Newton started his teaching career in the Mathematics Department at the University of Illinois Champaign-Urbana (UIUC) and at the Center for Complex Systems Research (CCSR) at the Beckman Institute, where he became an Assistant (1987) and then Associate Professor (1993). In 1993 he moved to the Aerospace & Mechanical Engineering Department and the Mathematics Department at the University of Southern California and was promoted to Full Professor in 1998. He is currently a Professor in the Viterbi School of Engineering (AME), Dornsife College (Mathematics) and Keck School of Medicine (Norris Comprehensive Cancer Center) at USC. He is also Editor-in-Chief of the Journal of Nonlinear Science (SpringerNature).

For the last 10 years, Professor Newton's work and funding has been primarily in the field of computational health sciences, mathematical oncology, medical biophysics, and systems biology. His focus has been primarily on using longitudinal patient data to build quantitative and predictive mathematical and computational dynamical systems models of metastatic cancer progression and the dynamics and control of the tumor- immune ecosystem. His entry into this field began when he functioned as Co-PI on one of the 12 original National Physical Sciences Oncology Centers funded by the National Cancer Institute (NIH) located at The Scripps Research Institute in La Jolla CA. The center’s title was ‘The Physics and Mathematics of Metastasis over Time and Space’ (2009-2014) where he functioned as head of the mathematical modeling group. During that time period, he focused intensively on learning all aspects of the disease, including the biology and genetics of cells and organisms, population genetics, tumor suppressor genes and oncogenes, tumor growth models, invasion and metastasis, tumor immunology and immunotherapy, chemotherapy scheduling, chemotherapeutic resistance and clinical trial design, with the goal of developing ways to add value to the field of medical oncology using mathematical tools.

In 2018 (June-July) he was a Visiting Scientist in the Integrative Mathematical Oncology Department at the Moffitt Cancer Center, Tampa Florida. He currently focuses on using evolutionary game theory models to optimize chemotherapy and immuno-chemotherapy schedules, understanding how heterogeneous collections of cancer cells cooperate to produce volumetric growth and on using Markov chain and network dynamics models to develop predictive metastasis models of breast, prostate and lung cancer. He is generally interested in analyzing all types of medical data in order to extract patterns and build low-dimensional predictive models that help physicians and patients.

Professor Newton received his B.S. (cum laude) degree in Applied Mathematics/Physics at Harvard University in 1981 and his M.S. (1982) and Ph.D. (1986) in the Division of Applied Mathematics at Brown University. He then moved to the Mathematics Department at Stanford University to work as a post-doctoral scholar under J.B. Keller.

At the Ellison Institute, Dr. Newton is one of 10 affiliate members.

For the last 10 years, Professor Newton's work and funding has been primarily in the field of computational health sciences, mathematical oncology, medical biophysics, and systems biology. His focus has been primarily on using longitudinal patient data to build quantitative and predictive mathematical and computational dynamical systems models of metastatic cancer progression and the dynamics and control of the tumor- immune ecosystem. His entry into this field began when he functioned as Co-PI on one of the 12 original National Physical Sciences Oncology Centers funded by the National Cancer Institute (NIH) located at The Scripps Research Institute in La Jolla CA. The center’s title was ‘The Physics and Mathematics of Metastasis over Time and Space’ (2009-2014) where he functioned as head of the mathematical modeling group. During that time period, he focused intensively on learning all aspects of the disease, including the biology and genetics of cells and organisms, population genetics, tumor suppressor genes and oncogenes, tumor growth models, invasion and metastasis, tumor immunology and immunotherapy, chemotherapy scheduling, chemotherapeutic resistance and clinical trial design, with the goal of developing ways to add value to the field of medical oncology using mathematical tools.

In 2018 (June-July) he was a Visiting Scientist in the Integrative Mathematical Oncology Department at the Moffitt Cancer Center, Tampa Florida. He currently focuses on using evolutionary game theory models to optimize chemotherapy and immuno-chemotherapy schedules, understanding how heterogeneous collections of cancer cells cooperate to produce volumetric growth and on using Markov chain and network dynamics models to develop predictive metastasis models of breast, prostate and lung cancer. He is generally interested in analyzing all types of medical data in order to extract patterns and build low-dimensional predictive models that help physicians and patients.

Professor Newton received his B.S. (cum laude) degree in Applied Mathematics/Physics at Harvard University in 1981 and his M.S. (1982) and Ph.D. (1986) in the Division of Applied Mathematics at Brown University. He then moved to the Mathematics Department at Stanford University to work as a post-doctoral scholar under J.B. Keller.

At the Ellison Institute, Dr. Newton is one of 10 affiliate members.