Boyu Peng is an Adjunct Instructor in Health Data Analytics at the MGH Institute of Health Professions, where he serves as a key advisor to faculty on the application of computer vision, machine learning, and advanced programming methods in healthcare research.
Mr. Peng’s academic and research interests focus on advancing translational science through the application of artificial intelligence, machine learning, and computer vision. His expertise includes developing deep learning models for pattern recognition, probabilistic modeling to reduce diagnostic uncertainty, and computer vision algorithms capable of extracting clinically relevant features from complex datasets such as video and sensor data. He is particularly focused on establishing rigorous data standards, reproducibility frameworks, and transparent pipelines that enable AI methods to be interoperable, auditable, and aligned with regulatory and translational requirements. By combining technical depth in algorithm development with a commitment to standards-driven design, Mr. Peng’s work supports the reliable integration of AI into biomedical and healthcare research.
Mr. Peng has co-authored multiple peer-reviewed publications, including recent work in The American Journal of Emergency Medicine and JMIR Formative Research. In addition, he serves as a reviewer for conferences and journals in digital health .
Through these contributions, Mr. Peng plays a critical role in bridging advanced computational methods with the practical needs of healthcare and biomedical research.
- MS, Computer Science, University of Southern California
- BS, Computer Engineering, Michigan State University
Expert in AI, computer vision, and data standards for translational biomedical research
View a listing of Boyu's scholarly work on his Google Scholar profile.