PhD-Viterbi School of Engineering, University of Southern California


Dr. Mason received his BS in 2009 in Mechanical Engineering from the Georgia Institute of Technology. Immediately after graduation, he began a doctoral program at USC’s Viterbi School of Engineering. His research work focused on utilizing patient data collected from a large autopsy study to develop stochastic Markov chain models of cancer metastasis for 12 primary cancer types, including breast, lung, prostate, and ovarian. After receiving his PhD in 2013, Dr. Mason continued his research in mathematical oncology at The Scripps Research Institute before shortly moving back to USC as a postdoctoral scholar at the Convergent Science Initiative in Cancer (CSI-Cancer) within USC’s Dorsnife College of Letters, Arts and Sciences. Here he would develop additional models of cancer metastasis from more recent, longitudinal datasets of primary breast cancer, lung cancer, and bladder cancer. Additionally, Dr. Mason became a fellow at the United States Department of Veterans Affairs (VA) through the Big Data-Scientist Training Enhancement Program (BD-STEP) where he developed a prediction model utilizing veteran patient data. In August 2018, Dr. Mason joined the Department of Urology at the Keck School of Medicine of USC as an Assistant Professor of Research. He intends to focus his efforts on developing predictive models from longitudinal clinical, demographic, and research data to predict disease-related events throughout the course of disease and treatment on an individual patient basis. Simultaneously, he has also become an independent contractor with the United States Food and Drug Administration (FDA), where he will apply these techniques to phase 3 clinical trial data for approved cancer therapies.

NIH Funding Acknowledgment: Important - All publications resulting from the utilization of SC CTSI resources are required to credit the SC CTSI grant by including the NIH funding acknowledgment and must comply with the NIH Public Access Policy.