Cancer Technology & Data Science Program
Characterizing cancer’s spatial and molecular properties by advancing instrumentation, computing, and data science to transform cancer research and clinical care.
Program Leaders
Brian Cunningham
Professor
Electrical & Computer Engineering
Viktor Gruev
Professor
Electrical & Computer Engineering
Themes
1. Cancer Imaging
The Cancer Imaging Theme aims to advance the frontiers of imaging capability, providing new technologies that can interrogate fundamental molecular characteristics and that can make current apporaches more powerful and easier to use. A major direction is to enable co-recording of the spatial and molecular content of cancer.
2. Computational Engineering and Data Science
The Computational Engineering & Data Science Theme promotes new algorithms and computational methods that enable CTD’s technologies, improve understanding of cancer from multiple data streams, and model cancer processes. Using foundational advances, the work enables practical applications like optimizing drug discovery or new research opportunities in detection and diagnoses, therapeutics, and modeling.
3. Molecular Measurement
The Molecular Measurement Theme seeks to understand the molecular drivers of cancer processes and use the knowledge for better cancer detection. A major direction is to provide easy to use molecular sensing tools that can be deployed for wide access and provide actionable information at the point of care.