Machine QA
Exposure to the quality assurance processes that support safe, reliable treatment delivery.
CurrentPhD Candidate, Medical Biophysics
InstitutionUniversity of Toronto
Career focusClinical Medical Physics
Professional focus
Bridging rigorous clinical practice with responsible innovation.
01Profile
From computational research to clinical medical physics.
I am a PhD candidate in Medical Biophysics at the University of Toronto, working at the intersection of artificial intelligence, radiation therapy, and medical imaging.
My interests have expanded from developing computational methods to understanding how complex technologies are safely validated, implemented, and maintained in clinical practice.
My goal is to contribute not only to new technologies, but to their careful validation and safe use in patient care.
02Clinical Medical Physics
Clinical insight grounded in patient safety.
During a 2026 Radiation Oncology observership at Gangnam Severance Hospital in Seoul, I gained exposure to the systems, checks, and multidisciplinary decisions behind modern treatment delivery.
Patient-Specific QA
Experience observing verification workflows designed around treatment accuracy and patient safety.
Treatment Planning
Clinical perspective on plan development, chart review, and adaptive radiotherapy workflows.
MR-Guided Radiotherapy
Focused interest in the Elekta Unity MR-Linac and the integration of imaging with adaptive treatment.
Particular interest: adaptive radiotherapy and the Elekta Unity MR-Linac.
Discuss clinical interests03Selected Research
Research designed around clinical questions.
A curated view of work spanning dose prediction, treatment planning, multimodal learning, and medical imaging.
01
Dose prediction
GRADIENT
Text-conditioned radiotherapy dose prediction across multiple treatment protocols and disease sites.
Selected work
02
Treatment planning
Multi-Task Radiotherapy Learning
Combining organ segmentation and voxel-level dose prediction within a unified learning framework.
Selected work
03
AAPM 2026
AI-Based Therapy Planning
Research on artificial intelligence methods for radiation therapy planning and their clinical context.
Selected work
04
Clinical data
Multimodal Medical AI
Learning across medical imaging, clinical text, ECG, and other modalities to support richer clinical models.
Selected work
05
Imaging research
Medical Imaging
Computational approaches that connect medical image analysis with clinically meaningful questions.
Selected work
06
Future focus
Safe Clinical Translation
Responsible validation and implementation of AI within quality-conscious radiation oncology workflows.
Selected work04Trajectory
Education & experience
A research-intensive path increasingly
focused on the safe clinical implementation
of advanced technologies in radiation oncology.
Education
PhD Candidate in Medical Biophysics
University of Toronto
Doctoral research in artificial intelligence for radiation therapy, treatment planning, dose prediction, multimodal learning, and medical imaging.
Verified experience
Clinical Experience · 2026
Radiation Oncology Observership
Gangnam Severance Hospital · Seoul, South Korea
Exposure to machine QA, patient-specific QA, treatment planning, chart review, adaptive workflows, and MR-guided radiotherapy.
Verified experience
Professional Direction
Clinical Medical Physics
Radiation Oncology
Preparing to combine rigorous clinical training with research and technological innovation, with patient safety at the center.
Verified experience
05Research Output
Publications, presentations & code
For a current, verified record of publications and
conference activity, visit my academic and professional profiles.
Awards & scholarships
A verified record will be added as the portfolio is updated.
Professional service
Service details will be published when the full CV is available.
Curriculum Vitae
A complete record, coming soon.
The CV download will be activated when the final PDF is available. In the meantime, explore the verified profiles above.
06Contact
Let’s connect around clinical medical physics.
I welcome conversations with residency programs, clinical medical physicists, and academic collaborators.