Professor Melvyn Sim proposes a joint estimation and robustness optimization (JERO) framework to mitigate estimation uncertainty in optimization problems by seamlessly incorporating both the parameter estimation procedure and the optimization problem in “Joint Estimation and Robustness Optimization”

Professor Chaithanya Bandi presents an optimization model to address the inefficiency of intraday scheduling problem in a group of orthopaedic clinics, such as long patient waiting time and physician overtime, in “Intraday Scheduling with Patient Re-entries and Variability in Behaviours”

Professor Lucy Chen examines co-opetition in a service setting, develops a novel model of waiting-area entertainment and sheds new light on the emerging practice of service clusters and small-footprint retailing in “Co-Opetition in Service Clusters with Waiting-Area Entertainment”.

Professor Chen Zhi presents a model for combining point forecasts into a predictive distribution for a variable of interest and shows that ignoring dependence or parameter uncertainty can lead to assuming an unrealistically narrow predictive distribution in “Assessing Uncertainty from Point Forecasts”.

Professor Mabel Chou demonstrates how analytical tools can help achieve significant improvements in both patient service and resource utilization without the need to increase the overall level of existing capacities in “Analytics for Hospital Resource Planning—Two Case Studies“

Professor Feng Yifan studies how to sequentially display subsets of variants to potential consumers, so that the company can quickly learn the best variant from consumer choices in “Robust Learning of Consumer Preferences“.