I am a researcher at The University of Texas MD Anderson Cancer Center, where I lead research on radiomics and imaging biomarkers to predict cancer treatment outcomes using state-of-the-art machine and deep learning methods.
My work spans the full computational imaging pipeline — from data acquisition and curation using PACS, EPIC, and XNAT systems to developing novel deep learning models for early prediction of treatment outcomes, toxicities, and biomarker statuses in cancer patients.
I actively collaborate with radiologists and clinical investigators to translate computational imaging research into clinically meaningful tools. I also serve as an academic editor for PLOS ONE, Frontiers in Oncology, and Frontiers in Nuclear Medicine, and have reviewed over 350 articles across 25+ high-impact journals.
My interdisciplinary background spans medical image analysis, cancer biomarker, Computer Vision, NLP, foundation models and large language models, making me well-suited for medical AI research challenges.