Investigator, Instructor RadOnc MGH BortfeldLab, Mass General Research Institute

Instructor in Radiation Oncology Harvard Medical School

Ph.D. University of Washington 2018

bayesian modeling; biomarker discovery; combined modality therapy; computational image analysis; digital health; image-guided radiotherapy; operations research; optimization; wearables

I develop computational methods to make cancer treatment more adaptive, personalized, and accessible. My research combines mathematical optimization, artificial intelligence, predictive modeling, and longitudinal patient data to support treatment decisions as patients respond to therapy. A central focus of my work is radiotherapy, where I study how imaging, physiologic signals, digital biomarkers, and treatment data can be used to detect evolving response and toxicity, update patient-specific risk, and identify opportunities for treatment adaptation.

My research spans three connected areas: monitoring treatment response, personalizing treatment based on emerging biological and clinical information, and improving the delivery of cancer care. Ongoing work includes wearable-based cardiovascular monitoring during radiotherapy, dynamic prediction of radiation-induced toxicity, longitudinal imaging biomarkers of tumor response, biologically informed treatment optimization, and optimization-based approaches to treatment scheduling and resource allocation. Across these efforts, my goal is to move computational methods beyond retrospective prediction toward prospective decision support and clinically deployable systems that improve both treatment quality and access.