Research
Our Research
Research Areas
Advanced Imaging
We develop and apply imaging methods to better understand cancer tissue properties, treatment response, and radiation therapy data. Our work emphasizes imaging approaches that can support clinical research and improve interpretation of disease and treatment effects.
Radiation Oncology Informatics
We build systems that organize, process, and visualize radiation oncology data, including imaging, treatment plans, dose distributions, structures, and clinical metadata. These tools help make complex treatment information more accessible for research and clinical review.
Artificial Intelligence and Data Science
We develop AI-enabled workflows for imaging analysis, segmentation, data visualization, and clinical decision support. Our goal is to apply artificial intelligence in ways that are practical, interpretable, and useful for oncology research.
Research Computing Infrastructure
We design and operate scalable computing systems that support large-scale imaging, AI, and clinical informatics workflows. This infrastructure enables reproducible research pipelines, GPU-enabled analysis, and efficient collaboration across research teams.
Research Computing Infrastructure
Brain Metastases Data Lake
A structured research data lake that organizes clinical, imaging, radiation therapy, and outcomes data for patients with brain metastases. The platform supports cohort discovery, longitudinal analysis, imaging review, treatment-response studies, and downstream AI and informatics research.
Scalable Compute and Storage
A distributed CPU/GPU research computing environment enables high-throughput imaging, treatment planning, segmentation, and clinical data workflows, supported by more than 300 TB of shared storage.
Workflow and Automation
Automated pipelines help retrieve, validate, process, and organize clinical and imaging data into standardized, analysis-ready formats.
Reproducible Research
Containerized tools, shared storage, and structured workflows support reproducible analysis across projects, datasets, and multidisciplinary research teams.