Uncovering the Hidden Wisdom of Crowds in Smart Cities
Data-driven intelligence is essential to the success of smart city initiatives. In this talk, we will review our recent studies in developing creative and practical solutions to emerging challenges in smart cities. By integrating a wide range of information and uncovering the hidden wisdom of crowds in smart cities, our data-driven techniques can benefit citizens, transportation services, business, and government agencies. Both algorithmic challenges and societal impacts will be discussed.
Dr. Chuanren Liu
Chuanren Liu is currently an Assistant Professor in the Decision Sciences and MIS Department at Drexel University.
He received the Ph.D. in Management (Information Technology) from Rutgers, the State University of New Jersey, USA, the M.S. degree in Mathematics from the Beijing University of Aeronautics and Astronautics (BUAA), and the B.S. degree in Mathematics from the University of Science and Technology of China (USTC). His research interests include data mining and knowledge discovery, and their applications in business analytics. He has published papers in refereed journals and conference proceedings, such as European Journal of Operational Research, Annals of Operations Research, INFORMS Journal on Computing, IEEE Transactions on Data and Knowledge Engineering, IEEE Transactions on Cybernetics, Knowledge and Information Systems and SIGKDD, ICDM, SDM, AAAI, IJCAI, UbiComp, IEEE BigData, etc.
Areas of expertise:
- Computational Finance
- Data Mining
- Health Informatics
- Knowledge Management
- Recommender Systems
- Sequential Pattern Analysis
- Social Mining
- Spatio-temporal Data Analysis
- Text Mining