Danielle Mowery, PhD, MS, MS, FAMIA



Danielle Mowery, PhD, MS, MS, FAMIA

Danielle Mowery, PhD, MS, MS, FAMIA

Assistant Professor of Informatics

Dr. Danielle Mowery is a collaborative investigator that develops natural language processing (NLP) solutions for processing clinical texts — i.e., clinical notes, chatbots, and transcribed texts — to support clinical and translational research. She leverages NLP, data science, and computational methods to integrate and analyze information from unstructured texts and structured clinical data to help clinical investigators better understand disease burden, treatment efficacy, and clinical outcomes. Furthermore, her solutions focus on helping patients and clinicians make better decisions at the point of care whether it's in a traditional health system setting or through digital health services within a patient’s home. Her work aims to uncover scientific discoveries, identify actionable healthcare knowledge, and optimize translation of research into patient care.

As the inaugural Chief Research Information Officer for Penn Medicine, she directs Clinical Research Informatics Core at the Institute for Biomedical Informatics — a key position designed to bridge the gaps between clinical data, research expertise, and actionable healthcare knowledge. Dr. Mowery represents Penn Medicine in local, regional, national, and international clinical research informatics communities, i.e., currently, serving as co-chair of the Penn Medicine AI Governance Committee, co-chair of the Association of American Medical Colleges (AAMC) Group on Information Resources (GIR), and member of the Epic Cosmos Governing Council.

Content Area Specialties

Natural language processing, electronic health records, data standards, patient phenotyping, biomedical informatics, clinical informatics, patient-centered outcomes research, clinical research services, clinical decision support, AI chatbots

Methodology Specialties

Data science, machine learning, rule-based systems, feature selection, data classification, data visualization

About Us

To understand health and disease today, we need new thinking and novel science —the kind  we create when multiple disciplines work together from the ground up. That is why this department has put forward a bold vision in population-health science: a single academic home for biostatistics, epidemiology and informatics. 

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