Cancer Technology and Data Science Program

Characterizing cancer’s spatial and molecular properties by advancing instrumentation, computing, and data science to transform cancer research and clinical care.

Aims

1. Develop next-generation imaging technologies to advance cancer research, diagnosis, and treatment.
2. Engineer advanced molecular detection methods for personalized cancer care.
3. Generate novel computational analyses for cancer research and care, developing tools to extract, store, and manage knowledge from diverse data sources.
4. Nurture a diverse pipeline of talented scientists in cancer research.

Program Leaders

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.