Hanieh Razzaghi, PhD

Dr. Hanieh Razzaghi is an informatics researcher focused on advancing the quality as well as reproducibility and replicability of clinical data for research within learning health systems and multi-institutional research networks. Her work centers on developing systematic, scalable approaches to assessing data fitness, along with the knowledge representation infrastructure, that makes clinical data and research artifacts findable, interoperable, and reusable across studies. She is interested in how emerging methods in AI and machine learning can be applied to improve data quality assessment, integrate multi-modal data, and support more efficient, reproducible research at scale. Dr. Razzaghi is also focused on developing frameworks that support research replicability and reproducibility more broadly, including standardized approaches for documenting and reporting the data curation decisions that shape study findings. Her recent work extends to exploring the use of AI and large language models in extracting clinical information from clinical notes and images to complement structured EHR data. Her frameworks and tools have been adopted across national research networks, shaping how these networks assess and report data quality, and her findings have informed clinical guidance on topics ranging from pediatric outcomes to chronic and rare disease management.

Dr. Razzaghi earned her PhD in Information Science from Drexel University’s College of Computing & Informatics and her MPH in from the Yale School of Public Health. She serves as the Director of Analytics for the PEDSnet Data Coordinating Center at the Children’s Hospital of Philadelphia (CHOP). She has lectured widely on data quality and learning health systems, and continues to bridge the gap between data and evidence to increase trust in real-world data for improving patient care.