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Domain of ResearchIntegration and the management of disparate information, i.e. the integration and management of multi-modal and multimedia information from distributed, heterogeneous, and autonomous sources
Stéphane Bressan is Associate Professor in the Department of Computer Science of the School of Computing (SoC) at the National University of Singapore (NUS). Stéphane is Track leader for Maritime Information Technologies at NUS Centre for Maritime Studies (CMS). He is Affiliate Professor at NUS Business Analytics Centre. He is researcher at Image & Pervasive Access Lab (IPAL) (Singapore-France CNRS UMI 29255). Stéphane's research interest is the integration, management and analysis of data from heterogeneous, disparate and distributed sources.
He is the author of more than 100 articles in international peer reviewed conferences and journals. He is member of the steering committee of the Database Systems for Advanced Applications conference series (DASFAA) and founding and steering committee member of the International Organization for Information Integration and Web-based Applications & Services (@WAS). He serves on the committees of numerous international peer reviewed conferences and journals.
Stéphane graduated in 1987 with a degree in Computer Science, Electronics and Process Automation from the Ecole Universitaire D'Ingénieurs de Lille (France) (now Polytech Lille ) and received his Master and his Ph.D. in Computer Science in 1988 and 1992, respectively, from the Laboratoire D'informatique Fondamentale of the University of Lille (France). In 1990, Stéphane joined the European Computer-industry Research Centre (ECRC) of Bull, ICL, and Siemens in Munich (Germany). In 1994, he was appointed site Leader of the Database Platform project and Principal Investigator and Work-package Manager for the European IDEA ESPRIT project on Intelligent Databases. From 1996 to 1998, he was Research Associate at the Sloan School of Management of the Massachusetts Institute of Technology (MIT) (United States of America).
Keynote Title: Moving the Cheese: Designing Spatio-temporal Collaborative Crowd Sourcing Platforms
From Amazon Mechanical Turk and Uber, to TaskRabbit and Go-Jek, crowd and manpower sourcing is defining a new labour economy. In “Who Moved My Cheese? An Amazing Way to Deal with Change in Your Work and in Your Life” Spencer Johnson metaphorically commented on change and adaptiveness. Crowd sourcing and the Uberization of the economy create one major disruption unfolding in front of our eyes. It is time to harness the challenges and devise algorithms that make this new labour distribution and management paradigm sustainable and, more specifically, equitable. Crowd sourcing platform must balance the workload, costs and benefits among the platform operator, the requesters and the workers.
Crowdsourcing is an activity consisting in outsourcing tasks to a community of online, yet on-ground and mobile, workers. A spatio-temporal collaborative task is characterized by the requirement that a set of workers meeting some complementary skills requirements must move from their current location to a specified location to accomplish the task under some time constraints.
In this presentation we discuss selected issues and challenges in the design and implementation of effective, efficient and equitable spatio-temporal collaborative crowdsourcing platforms. We examine pricing mechanisms, their truthfulness and their social fairness as well as the management of uncertainty.