the Advisory Council

Pei-Yun Sabrina Hsueh

Pei-Yun Sabrina Hsueh (Ph.D., FAMIA) is the Director of Ethical AI and External Innovation at Pfizer. With 15 years of experience in innovating and operationalizing health AI solutions, public-private partnerships, and innovation strategies, she is a global leader in the industry's best practices of health AI. Her expertise lies in establishing a responsible AI governance framework and productizing AI in workflows. 

Sabrina serves on the Practitioners Board of the Association of Computing Machinery (ACM) and as the American Medical Informatics Association (AMIA) AI Evaluation Showcase 2023 Co-Chair. In AMIA, she is the incoming co-chair of the Women in AMAI steering committee and a member of the Public Policy Committee. She organizes the AMIA-DCI conference on Trustworthy AI and is part of the workgroup of Real-World Data for AI.

In her previous roles, she was the Vice-Chair of the AMIA SPC 2022, Co-Chair of the KDD Applied Data Science in Healthcare Workshop, and the past chair of the Consumer Health Informatics Work Group. Sabrina leads a series of initiatives in AI Evaluation and Governance and real-world evidence strategy with cross-functional teams. She has also co-chaired the Health Informatics Professional Community at IBM Research and served on the IBM Academy of Technology.

Sabrina's dedication to patient voices and responsible health AI has earned her numerous recognitions, including distinguished paper and invention awards, as well as recognitions from corporations for her eminence and management contributions. She has hosted special issues on Sensors Journal, Frontiers in Public Health, Journal of Health Informatics Research, and JAMIA OPEN Special Issue on Precision Medicine and AI Evaluation.

Sabrina received her Ph.D. in Computer Science from Edinburgh University and her Master's degree from the University of California, Berkeley, with a focus on NLP and HCI. Her commitment has resulted in 20+ patents, 50+ technical articles, and two new textbooks: "Machine Learning for Medicine and Healthcare" (in prep.) and "Personal Health Informatics - Patient Participation in Precision Health" (published by Springer Nature in 2023).


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