SIMT SRS
Prediction and analysis of normal-brain dose-volume metrics for single-isocenter multi-target stereotactic radiosurgery.
Medical Physics · Research · Software
Zhuoyun Huang
Medical Physics PhD Student
University at Buffalo
Radiation Oncology · Machine Learning · Medical Imaging
I develop research methods and clinical software at the intersection of medical physics, radiation therapy, imaging, and machine learning.
About
About Me
I earned my M.S. in Medical Physics from Duke University and am pursuing doctoral training in Medical Physics at the University at Buffalo.
My work focuses on radiation oncology, stereotactic radiosurgery, medical imaging, machine learning, and clinical software development. I am particularly interested in translating data-driven research into practical tools for treatment planning, plan evaluation, and patient care.
Research
Research Interests
Machine Learning
Gradient-boosted tree models and data-driven methods for treatment-planning prediction and clinical decision support.
Clinical Software
Development of software tools for plan analysis, workflow automation, and medical physics research.
Publications
Selected Publications
Journal Article
Predicting Normal Brain Dose-Volume Metrics for Single-Isocenter Multi-Target Stereotactic Radiosurgery
Zhuoyun Huang et al.
Journal of Radiosurgery and SBRT
Accepted for publication
Projects
Selected Projects
Selected research, clinical software, and educational projects involving medical physics, machine learning, and web development.
SRS Dose Prediction
Machine learning framework for predicting normal-brain dose-volume metrics in single-isocenter multi-target stereotactic radiosurgery.
MATLABMachine LearningMedical PhysicsSRS
View Repository →Arc Analysis for Eclipse ESAPI
Interactive Eclipse ESAPI application for VMAT arc MU/degree analysis, polar visualization, and automatic arc avoidance detection.
C#ESAPIVMATWPF
View Repository →AI Medical Physics Platform — In Development
AI-powered platform for medical physics education featuring interactive notes, question banks, formulas, and intelligent explanations.
Next.jsTypeScriptAI
View GitHub Profile →Personal Website
Personal academic website built with Next.js and Tailwind CSS to showcase research, publications, software projects, and professional experience.
Next.jsTailwind CSSTypeScript
View Repository →