Y.H. Kuo

Assistant Professor
Email:yhkuo@hku.hk
Tel:**
Office:HW 8-8

Biography

Dr. Yong-Hong Kuo is Assistant Professor in the Department of Industrial and Manufacturing Systems Engineering, the University of Hong Kong. He earned his B.Sc. in Mathematics, with a minor in Risk Management Science, and M.Phil. and Ph.D. in Systems Engineering and Engineering Management, from the Chinese University of Hong Kong. During the period, he also worked at the University of California at Berkeley as Visiting Researcher and Oak Ridge National Laboratory as Visiting Student. Prior to joining HKU, he was Research Assistant Professor at Stanley Ho Big Data Decision Analytics Research Centre, the Chinese University of Hong Kong.
Dr. Kuo'scurrent research focus is on the integration of systems modelling, discrete optimization, and data analytics for solving decision-making problems in service systems, where most of his applications are in the domains of logistics and transportation services and healthcare service delivery. He isinterested in modelling problems, devising solution procedures, and using these tools to improve operations, help system design, and derive managerial insights. His research, with his role as Principal Investigator, has been supported by a number of funding agencies, including Hong Kong Research Grants Council, Health and Medical Research Fund, Microsoft Research Asia, and Macao Science and Technology Development Fund.Hissolution methodologies and applications have been published in top journals in various fields, including industrial engineering, operations management, transportation, and healthcare informatics. He has served on the Editorial Advisory/Review Boards ofDecision Sciences Journal andTransportation Research Part Eand as Managing Guest Editor for several academic journals.
Personal website: https://sites.google.com/site/yonghongkuo/

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?Research Interests

Discrete optimization
Data-intensive modeling and optimization techniques
Systems simulation
Logistics and transportation planning
Healthcare service delivery

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Courses

IMSE3136Operations Planning and Control
IMSE4136 Transportation and Distribution Planning

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Selected Publications

* indicates the corresponding author
Wang X., Kuo Y.H., Shen H., and Zhang L.* “Target-oriented robust location–transportation problem with service-level measure." Transportation Research Part B: Methodological, 153: 1–20, 2021.
Nasir J.A. andKuo Y.H.* “A Decision Support Framework for Home Health Care Transportation with Simultaneous Multi-Vehicle Routing and Staff Scheduling Synchronization." Decision Support Systems, 138: 113361, 2020.
Kuo Y.H.*, Chan N.B., Leung J.M.Y., Meng M., So A.M.C., Tsoi K.K.F. andGraham C.A., "An Integrated Approach of Machine Learning and Systems Thinking for Waiting Time Prediction in an Emergency Department." International Journal of Medical Informatics, 139: 104143, 2020.
Kuo Y.H. and Kusiak A.*, “From Data to Big Data in Production Research: The Past and Future Trends.", International Journal of Production Research, 57(15-16): 4828–4853, 2019. (Top cited paper published in 2019; Selected Surveys on Cutting-edge Problems in Production Research)
Ho S.C., Szeto W.Y.*, Kuo Y.H., Leung J.M.Y., Petering M. andTou T.W.H., “A Survey of Dial-a-ride Problems: Literature Review and Recent Developments." Transportation Research Part B: Methodological, 111: 395–421, 2018.(Most cited paper published since 2018)
Cheng C.H. and Kuo Y.H.*, “A Dissimilarities Balance Model for a Multi-skilled Multi-location Food Safety Inspector Scheduling Problem." IIE Transactions, 48(3): 235–251, 2016.
Kuo Y.H.* and Leung J.M.Y., “On the Mixed Set Covering, Packing and Partitioning Polytope." Discrete Optimization, 22(A): 162–182, 2016.
He S.Y.*, Kuo Y.H. and Wu D., “Incorporating Institutional and Spatial Factors in the Selection of the Optimal Locations of Public Electric Vehicle Charging Facilities: A Case Study of Beijing, China." Transportation Research Part C: Emerging Technologies, 67: 131–148, 2016.
Kuo Y.H., Leung J.M.Y.* and Yano C.A., “Scheduling of Multi-Skilled Staff Across Multiple Locations." Production and Operations Management, 23(4): 626–644, 2014.