MUST School of Business (MSB), in collaboration with the Faculty of Innovation of Engineering and the Medical Sciences Division, has successfully organized “When Less is More: Optimizing Prescription Alerts under Fatigue” research seminar at N101 Hall of MUST on 20 March 2025. Doctor Michael Lingzhi Li, Assistant Professor of Harvard Business School, was invited to be the distinguished speaker.
Welcome speech delivered by Professor Felix Tung Sun Chan, Vice Dean of MSB
Notable guests attending the research seminar included: Chair Professor Joseph Hun-wei Lee, Vice Chancellor and President of MUST; Chair Professor Paul Kwong-Hang Tam, Vice President of MUST and Chairman of Medical Sciences Division Board; Chair Professor Yi Zhun Zhu, Associate Vice President of MUST and Director of School of Pharmacy; Chair Professor Du Zhang, Director of School of Computer Science and Engineering; Professor Ni Sheng, Dean of MSB; Professor Cheng Kun Liu, Director of The Institute for Sustainable Development; Professor Felix Tung Sun Chan, Vice Dean of MSB; Professor Nivritti Gajanan Patil, Vice Dean of Faculty of Medicine, with over 300 teachers and students. During the research seminar, President Lee presented souvenir to Professor Li in recognition of his inspiring sharing.
President Joseph Hun-wei Lee (right) presented souvenir and took photo with Doctor Michael Lingzhi Li (left)
Group photo of the notable guests
Keynote speech by Doctor Michael Lingzhi Li
Doctor Michael Lingzhi Li graduated from Massachusetts Institute of Technology, and is currently an Assistant Professor in the Technology and Operations Management Unit at Harvard Business School. His research combines machine learning, data analysis and operations research to solve practical problems in the healthcare system. During the research seminar, Doctor Li delivered a compelling themed presentation on optimizing Computerized Provider Order Entry (CPOE) alert systems. His innovative fluid model, designed to optimize CPOE alert strategies under pharmacist fatigue, showed an 8 – 9% reduction in patient risk and a 40 – 50% decrease in unnecessary alerts. The session inspired vibrant exchanges on the future of human-AI collaboration in healthcare operations.
Several participating professors raised in-depth questions after the themed presentation in terms of the research models and application scenarios, which stimulated transformative discussions on leveraging technology to enhance healthcare systems. MUST will continue to launch relevant academic activities and build up an international cutting-edge exchange platform for teachers and students.
Participating scholars actively raised questions about the topic after keynote speech
(Contributed and reviewed by Assistant Professor Tony U, format reviewed by Helen Kam)
