Mosaic
Digital pathologyEstablishing digital pathology as a complement to—rather than surrogate for—sequencing in the context of tumor subtyping
Supported by ICI and aiTDIF. Featured at AACR AI and ESMO AI.
Things I’m building
Orpheus
Multimodal AICombining clinical text and pathology slides to identify high-risk breast cancer and generate synthetic images conditioned on risk.
Mussel
Research infrastructureScalable preprocessing for digital pathology. Built with Raymond Lim.
Selected papers & earlier work
Harnessing multimodal data integration to advance precision oncology
Roadmap to develop multimodal AI for oncology.
Simplifying clinical use of TCGA molecular subtypes through machine learning models
Consistent tumor subtype identification with parsimonious genomic data.
Late-fusion multimodal AI to risk stratify ovarian cancer
Combining histopathology, radiology, and clinicogenomics for ovarian cancer prognosis.
Predicting peptide presentation by major histocompatibility complex class I
Improved deep learning for MHC class I peptide presentation.
Resonance
Annual science conference connecting Yale researchers with New Haven high schoolers.
About
I’m in my final year of radiation oncology residency and postdoc in Computational Oncology, working with Nikolaus Schultz, Francisco Sanchez-Vega, and Sohrab Shah. My research is supported by an NCI K99/R00 Pathway to Independence Award.
Routine cancer care produces pathology slides, sequencing panels, and clinical records. I build models that connect these data to understand tumor biology and predict response to therapy.
Background
Tri-Institutional MD–PhD Program · Yale Biomedical Engineering · TJHSST
Affiliations
Current
Previous
- MSK Transitional Year
- Tri-Institutional Computational Biology PhD Program
- Tri-Institutional MD-PhD Program
- Yale Biomedical Engineering
- TJHSST
Other interests
Bodybuilding, techno, gaming, fantasy books, and green tea.
Languages
English Native · Spanish Professional · Japanese Intermediate · Swedish Beginner