AI and Analytics for Smart Cities and Service Systems Proceedings of the 2021 INFORMS International Conference on Service Science

2. Should Managers Care About Intra-Household Heterogeneity?

3. Penalizing Neural Network and Autoencoder for the Analysis of Marketing Measurement Scales in Service Marketing Applications

4. Prediction of Gasoline Octane Loss Based on t-SNE and Random Forest

5. Introducing AI General Practitioners to Improve Healthcare Services

6. A U-Net Architecture Based Model for Precise Air Pollution Concentration Monitoring

7. An Interpretable Ensemble Model of Acute Kidney Disease Risk 

8. Algorithm for Predicting Bitterness of Children's Medication

9. Intelligent Identification of High Emission Road Segment Based on Large-Scale Traffic Datasets

10. Construction Cost Prediction for Multi-family Housing Projects based on Support Vector Regression

11. Evolution of Intellectual Structure of Data Mining Research Based on Keywords

12. Development of a Cost Optimization Algorithm for Food and Flora Waste to Fleet Fuel (F4)

13. A Comparative Study of Machine Learning Models in Predicting Energy Consumption

14. Simulation Analysis on the Effect of Market-Oriented Rental Housing Construction Policy in Nanjing

15. Accidents Analysis and Severity Prediction Using Machine Learning Algorithms

16. The Use of Binary Choice Forests to Model and Estimate Discrete Choices

17. Prediction and Analysis of Chinese Water Resource: A System Dynamics Approach

19. Research on Hotel Customer Preferences and Satisfaction Based on Text Mining: Taking Ctrip Hotel Reviews as an Example

20. The Power of Analytics in Epidemiology for COVID 19: Prediction, Prevalence, and Vaccine Allocation

21. Electric Vehicle Battery Charging Scheduling Under the Battery Swapping Mode

22. Information Design for E-Consult Between Vertically Competing Healthcare Providers

23. Order Batching Problem in O2O Supermarkets

24. Integrating Empirical Analysis into Analytical Framework: An Integrated Model Structure for On-Demand Transportation

25. Patient Transfer Under Ambulance Offload Delays: An Approximate Dynamic Programming Approach

26. COVID-19 Epidemic Forecasting and Cost-Effectiveness Analysis: A Case Study of Hong Kong

27. Crowdsourcing Electrified Mobility for Omni-Sharing Distributed Energy Resources

28. Covid-19 Intervention Policy Optimization Using a Multi-Population Evolutionary Algorithm

29. Data-driven Joint Pricing and Inventory Management Newsvendor Problem

30. Additive Manufacturing Global Challenges in the Industry 4.0 Era

31. Broadening the Scope of Analysis for Peer-To-Peer Local Energy Markets to Improve Design Evaluations: An Agent-Based Simulation Approach

Robin Qiu, a full professor of information science, teaches a variety of courses on e.g. predictive analytics, management science, business process management, decision support systems, project management, enterprise integration, enterprise service computing, software engineering, Web-based systems, distributed systems, computer architecture/SOA, computer security, Web security, operations research, and system engineering. His research interests include big data, data/business analytics, smart service systems, service science, service operations and management, information systems, and manufacturing and supply chain management.

 

Kelly Lyons is a professor at the Faculty of Information, University of Toronto with a cross appointment to the Department of Computer Science. Prior to joining the Faculty of Information, she was the program director of the IBM Toronto Lab Centre for Advanced Studies (CAS). Her current research interests include service science, knowledge mobilization, data science, social media, and collaborative work. From 2015 to 2020, she served as an associate dean, Academic at the Faculty of Information. From 2020 to 2021, she is serving as the dean’s advisor on Pandemic Planning and Response. She has co-authored several papers, served on program committees for conferences, given many keynote and invited presentations, and co-chaired several workshops. She has received an NSERC Strategic Partnership Grant, NSERC Discovery Grants, an NSERC Collaborative Research and Development Grant with SAP, two NSERC Engage Grants (with ScienceScape and Dell), MITACS Accelerate Grants (with CA, IBM, and Cerebri AI), an SSHRC Knowledge Synthesis Grant, and an IBM Smarter Planet Faculty Innovation Grant, as well as funding from the GRAND Networks of Centers of Excellence (NCE). She is an IBM faculty fellow and a faculty affiliate of the Schwartz Reisman Institute for Technology and Society. She is currently on the Board of CS-Can/Info-Can and on the Board of the Informs Service Science Section. From 2008 to 2012, she was a member-at-large of the ACM Council and a member of the Executive Council of ACM-W. 

 

Weiwei Chen is an associate professor at Rutgers University. His research interests lie in operations and finance interface, as well as supply chain operations planning and scheduling. He also works on simulation and randomized global optimization methodologies. He has extensive experience working with businesses and the public sector, especially in energy and healthcare, to improve strategic decisions and operational efficiency using data analytics.