Ali Ajdari, PhD.
Radiation Biophysicist · Mass General Cancer Institute
I develop computational methods for monitoring how patients respond to cancer treatment, adapting therapy as new information emerges, and improving how radiation oncology is delivered.
From observation to intervention.
Monitor
Measure treatment response as it evolves using physiological, imaging, and molecular signals.
Adapt
Translate evolving patient information into treatment decisions and personalized interventions.
Deliver
Develop systems that make better treatment decisions scalable, deployable, and accessible in clinical practice.
What we're working on now.
Digital biomarker-assisted cardiovascular monitoring
Continuous physiological monitoring during and after radiotherapy using wearable-derived cardiovascular biomarkers.
Dynamic cardiovascular risk prediction & intervention
Combining longitudinal heart-rate dynamics and cardiac dosimetry to identify evolving treatment-related cardiovascular risk.
Bi-level optimization for biologically informed radiotherapy
Integrating predictive outcome models into treatment planning while preserving clinically interpretable trade-offs.
Optimization for radiation oncology access
Decision-support systems for patient scheduling, machine allocation, capacity utilization, and timely access to treatment.
Selected recent work.
Computational methods for more responsive cancer care.
I am an investigator in radiation medical physics and computational oncology at Mass General Cancer Institute and Harvard Medical School. My work sits at the intersection of mathematical optimization, machine learning, longitudinal biomarkers, and radiation oncology, with an emphasis on methods that can ultimately be translated into clinical decision-making.