Dr. Haruka Itakura is an Assistant Professor of Medicine (Oncology) in the Stanford University School of Medicine, a data scientist, and a practicing breast medical oncologist at the Stanford Women’s Cancer Center. She is board-certified in Oncology, Clinical Informatics, Hematology, and Internal Medicine. Her research mission is to drive medical advances at the intersection of cancer and data science, applying state-of-the-art machine learning/artificial intelligence techniques to extract clinically actionable knowledge from heterogeneous multi-scale cancer data to improve patient outcomes. Her ongoing research to develop robust methodologies and apply cutting-edge techniques to analyze complex cancer big data was catapulted by an NIH K01 Career Development Award in Biomedical Big Data Science after obtaining a PhD in Biomedical Informatics at Stanford University. Her cancer research focuses on extracting radiomic (pixel-level quantitative imaging) features of tumors from medical imaging studies and applying machine learning frameworks, including radiogenomic approaches, for the integrative analysis of heterogeneous, multi-omic (e.g., radiomic, genomic, transcriptomic) data to accelerate discoveries in cancer diagnostics and therapeutics. Her current projects include prediction modeling of survival, treatment response, recurrence, and CNS metastasis in different cancer subtypes; detection of occult invasive breast cancer; and identification of novel therapeutic targets. Her ultimate goal is to be able to translate her research findings back to the clinical setting for the benefit of patients with difficult-to-treat cancers.