Jen Woo Yeon Park is a BIDS PhD candidate with several years of industry experience in healthcare data science. She is currently focusing on conducting health informatics research. Her research area is developing and evaluating the standardized integration of multimodal data (EHR, clinical notes, and imaging) to enhance the application of machine learning methods in precision medicine. Jen is passionate about empowering patients and clinicians through informatics framework and data science methods.
Jen’s academic career includes a Bachelor of Arts in Economics from University of California, San Diego, and a Master of Science in Business Analytics from University of Rochester. She has experience in healthcare data analytics in both hospital and health tech settings, including roles at Memorial Sloan Kettering Cancer Center and Blink Health.
As a BIDS PhD student, Jen has already had several important publications. Her newest paper, “Breaking Data Silos: Incorporating the DICOM Imaging Standard into the OMOP CDM to Enable Multimodal Research,” appears in this month’s issue of Journal of the American Medical Informatics Association (JAMIA). This work incorporates the Digital Imaging Communications in Medicine (DICOM) standard into the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) to represent imaging studies in multimodal research. This study focuses on mapping DICOM attributes to OMOP vocabularies and demonstrates real-world utility through an Alzheimer’s disease use case. Jen and her team hope this work provides a foundation for scalable, reproducible, and federated multimodal research.
According to Park, “Being part of the BIDS program has helped me grow from an applied data scientist into an informatics researcher who can think critically about data standardization and interoperability. The collaborative environment and mentorship have been instrumental in shaping my research direction.”
Jen’s advisor, Dr. Paul Nagy, is proud of her progress. “Jen is a star student whose research will ultimately improve personalized medicine,” says Nagy. “We can’t wait to see what she achieves next.”