Our lab is focused on translational AI for precision oncology. Our work spans across multiple data modalities including spatial transcriptomics/proteomics and histopathology. These data sets are linked with clinical outcomes to address unmet clinical needs. This can lead to improved cancer diagnosis and discovery of novel predictive biomarkers and therapeutic targets, which have the potential to transform cancer care.

We are developing new methods to make AI models more robust, reproducible, and interpretable, all of which are key elements of successful translational applications in medicine. A range of research topics are being investigated, including multi-modal foundation models and single-cell spatial biology for precision medicine.

Our research is multidisciplinary in nature. We work with a team of expert clinicians including oncologists, surgeons, and pathologists at Stanford and beyond. Our goal is to translate new technology and AI-based biomarkers to clinical practice, which will guide personalized cancer care and improve patient outcomes. 

Funding

Our lab is supported by multiple NIH R01 grants from the National Cancer Institute (R01CA269599, R01CA285456, R01CA290715) and the National Institute of Dental and Craniofacial Research (R01DE030894). Additionally, our work has been supported by the Stanford Institute for Human-Centered Artificial Intelligence (HAI) and Sanofi. My earlier research was supported by an NIH Pathway to Independence Award (K99/R00 CA166186) from 2012 to 2017.