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Ming-Chun Huang

Associate Professor of Data and Computation at Duke Kunshan University
DKU Faculty

Overview


Huang has a B.S (2007) in Electrical Engineering at Tsing Hua University, Taiwan, an M.S. (2010) in Electrical Engineering at the University of Southern California, and a Ph.D. (2014) in Computer Science at the University of California, Los Angeles. Prior to joining Duke Kunshan University in 2021, he was an Associate Professor at Case Western Reserve University (2014-2021). His research focus is the intersection among Precision Health and Medicine, Internet-of-Things, Machine Learning and Informatics, Motion and Physiological Signal Sensing. He had over 15 years of research experience conducting interdisciplinary scientific projects with researchers from distinct areas (e.g., Biomedical Engineering, Medicine, and Nursing). He had successfully administered past funded projects and productively published over a hundred peer-reviewed publications, 6 invention patents and software copyrights, and won 7 best paper awards/runner-up, 3000+ citations. His research has been reported in hundreds of high-impact media outlets. For the nature of richness and high impact of the research topics he was involved in, his research results in a plethora of new knowledge in aspects ranging from innovative IoT sensing technology, closed-loop AI analytics methodology, optimized clinical decision-making, and just-in-time patient risk assessment.

Current Appointments & Affiliations


Associate Professor of Data and Computation at Duke Kunshan University · 2021 - Present DKU Faculty

Recent Publications


Validating the information technology (IT) implementation framework to Implement mHealth technology for consumers: A case study of the Sense2Quit app for smoking cessation.

Journal Article International journal of medical informatics · October 2025 ObjectiveThe goal of this paper was to understand the applicability of the Information Technology (IT) Implementation Framework, a multi-level approach to identify factors that impede or promote IT usage, for incorporating a mHealth technology for ... Full text Cite

Feasibility and Acceptability of the Sense2Quit App for Improving Smoking Cessation in PWH.

Journal Article AIDS and behavior · June 2025 An estimated 34-47% of PWH in the US report cigarette smoking, three to four times the prevalence observed in the U.S. adult population. Given the dearth of smoking cessation interventions for PWH, our study team used community based participatory feedback ... Full text Cite

A Robust Cross-Platform Solution With the Sense2Quit System to Enhance Smoking Gesture Recognition: Model Development and Validation Study.

Journal Article Journal of medical Internet research · May 2025 BackgroundSmoking is a leading cause of preventable death, and people with HIV have higher smoking rates and are more likely to experience smoking-related health issues. The Sense2Quit study introduces innovative advancements in smoking cessation ... Full text Cite
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Education, Training & Certifications


University of California, Los Angeles · 2014 Ph.D.