Multimodal Medical Research
My research focuses on developing advanced AI methods for integrating and analyzing multimodal medical data. Working at Moffitt Cancer Center, I specialize in creating scalable frameworks that combine various data types to improve cancer diagnosis, prognosis, and treatment planning.
AI in Oncology
I develop deep learning models specifically designed for oncology applications, including survival prediction, treatment outcome forecasting, and biomarker discovery. My work includes foundation models and self-normalizing networks for multi-omics data analysis.
Clinical Data Extraction
I work on creating AI systems that can automatically extract structured information from unstructured clinical documents like pathology reports, enabling more efficient data processing for cancer registries and research databases.