Ali Ajdari

Ali Ajdari is an Instructor in Radiation Oncology at the Massachusetts General Hospital. With a Ph.D. in Optimization from the University of Washington and postdoctoral training in Radiation Therapy Optimization at Harvard Medical School, he applies operations research methodologies to healthcare, particularly oncology. His work bridges mathematical optimization, biological data, and clinical practice to advance personalized treatment plans.

• Education: B.Sc. and M.Sc. in Industrial & Systems Engineering, Ph.D. in Optimization

Research Interests focus on integrating optimization techniques (convex, robust, dynamic, stochastic) with medical data (imaging, genetic, bio-physiological) to enhance radiation therapy. His recent publications highlight applications in:

• Pediatric traumatic brain injury simulation
• Diffusion tensor-based target volume personalization
• Machine learning toxicity models in radiotherapy
• Mid-treatment adaptive planning using biomarkers

Publications Analysis reveals a strong emphasis on computational approaches in radiation oncology, with key contributions in:

• Anisotropic tumor volume modeling
• Online adaptive proton therapy
• Toxicity prediction frameworks
• PET/CT-driven treatment adaptation