CSDGC engages in multidisciplinary research that advances sustainable practices across multiple cultures, businesses, industries and economies. We strive to learn more about the cross-cultural implications of globalized growth and the implementation of strategies to facilitate environmentally sound progress.
Our research programs employ the latest theories and technologies to better address issues on urbanization, social and nature environment optimization, and business development to ensure economic growth within a healthy and sustainable context.
We have set our priority research goals to reflect our influential position at the crossroads of technological, industrial, economic and social advancement. These goals focus on empowering people and inspiring the mobilization of resources to create solutions for sustainable development.
Our current CSDGC research programs categorically focus on the following areas that aim to generate knowledge for a global society.
Smarter City and Smart Infrastructures
Urbanization and globalization have had a profound impact on city development during the last ten years. Rapid technological advancements and the emphasis on sustainability provide city planners and managers with more opportunities and challenges than ever before. A city composed of various operational systems, networks, infrastructures, and environments can be improved and optimized through the application of advanced technology solutions. A smart city is one that utilizes self-managing autonomic technologies to identify its functions and promote prosperity and sustainability. This kind of city involves one of the most promising city development strategies worldwide.
The first research project develops decision-support systems that both assess multidimensional levels of smartness for the current solutions of a city to environmental problems and recommend an optimal set of improvement strategies.
To better serve the design goal of a smart city, we also need to better understand how to build up smart infrastructures for a smart city. For the second research project, we develop an ontology-based service model for facilitating smart infrastructure design. This approach enables the design of specific smart infrastructures based on expected goals, availability of information, and the feasibility of implementation.
Another fundamental research problem on smart infrastructure is how to link physical infrastructures together to demonstrate smartness. For the third research project in this area, we focus on how to build sustainable infrastructures using a learning enabled cooperative multi-agent system approach. We propose an approach that uses information and communications technology (ICT) to enable physical infrastructures to better adapt and achieve sustainability goals. More specifically, we propose a framework to model sustainable infrastructures by employing a learning-enabled multi-agent system (LMAS) suitable for representing the functions of smart infrastructures.
Several papers have been published in reputable journals and IEEE conferences.
Cross-Cultural Learning, Decision Making, and Leadership for Smarter Organizations
We attempt to develop a better understanding of cross-culture and multidisciplinary based learning, decision making, and leadership development for smarter organizations. Focus will be put on how to more efficiently and effectively foster innovation and to develop better leaderships for smarter organizations. We hope this research will facilitate a conversation focusing on organizational decision making and behavior in an interdisciplinary (but disciplined) and cross cultural way in today’s global networked socity. The intention is scientific, to explore disciplinary and cultural differences in order to identify fundamental commonalities in processes of innovation. We also hope to develop a global research community for this research topic. A research workshop will be hosted at CSDGC in April 2013 to initiate the research community.
Sustainable Knowledge Resources and Social Computing
To make better decisions, we need to acquire more relevant information and knowledge. Simply put, we need to be knowledge savvy for our decisions. Due to rapid change of social and nature environments and accelerated pace of globalization and information over-loading, knowledge resources within an organization can become partially or completely obsolete rapidly. As such, we need to focus on making one very important resource, i.e., the knowledge resource, sustainable. We identify the following major research topics of sustainable knowledge resource:
Currently, we conduct research on using service-oriented computing as a major tool for developing sustainable knowledge resources. Services-oriented computing has revealed a new paradigm and brought technology revolution to traditional IT system development. As service technology has been developing rapidly, an increasing number of services are available on the Internet, and consequently terms such as Service Web and Internet of Services are proposed to describe this phenomenon. We propose a coupled matrix model to describe the multidimensional relationships among users, their information needs for decisions, and final optimized information services we can composed through available information resources, and we also design a factorization algorithm to predict unobserved relationships in the model to support more accurate service recommendation. The research will be published in the prominent artificial intelligence conference, the 23rd. International Joint Conference of Artificial Intelligence in August 2013.
- Continuously Knowledge Creation: In a fast changing global information age, information diffusion occurs rapidly, and thus the knowledge resource once you consider unique for competitiveness will be common sense within a short time period. Therefore, you have to create new knowledge continuously.
- Smart Knowledge Acquisition: Different knowledge resources have different quality and limitations. We need to understand what kind of knowledge to acquire and where to get it at the best cost.
- Maximizing Knowledge Reuse: To make frameworks for reuse of general knowledge for best-practices. In addition, developing approaches for classifying knowledge and the limitation of knowledge for future applications.
- Optimized Knowledge Application: Applying right knowledge at right time to right problems.
- Knowledge Ecosystem in a Global Information Age: Due to information over-loading, picking up right knowledge resources for your applications is demanding and critical for your future success. We need a system for systematically map various levels of knowledge recourse from an application, or user oriented view point. More specifically, we need to understand the life cycle assessment for knowledge resources, focusing on the dynamics of changing of knowledge resources and their applicability.
PUBLICATIONS AND CONFERENCE PRESENTATIONS
Tianshu Chu and Jie Wang, Management of Optimized Knowledge Diffusion and Creation in Organizational Structured Social Networks, Proceedings of the Third ASE International Conference on Social Informatics, Cambridge, MA, U.S.A., December 14-16, 2014.
Tianchu Chu, Jie Wang, and Jian Cao, Kernel-Based Reinforcement Learning for Traffic Signal Control with Adaptive Feature Selection, Proceedings of the 2014 IEEE Conference on Decision and Control, Los Angeles, CA, U.S.A., December 15-17, 2014.
Dingyu Yang, Jian Cao, Sai Wu, and Jie Wang, Progressive Online Aggregation in a Distributed Stream System， Journal of Systems and Software, accepted, 2014.
Shiyou Qian, Jian Cao, Yanmin Zhu, Minglu Li, and Jie Wang, H-Tree: An Efficient Index Structure for Event Matching in Content-based Publish/Subscribe Systems, IEEE Transactions on Parallel and Distributed Systems, accepted, 2014.
Jin Xin, Song Chen, Jie Wang, and Ting Wang, A Study of the Relationship Between the Knowledge Base and the Innovation Performance, 2014 Academy of Management Meeting, Philadelphia, Pennsylvania, August 1-5, 2014.
Xiaogang Wang, Jian Cao, and Jie Wang, An Agent-Based Dynamic Cloud Service Selection Strategy for Service Integration, 2014 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, Warsaw, Poland, 11-14 August, 2014.
Liang Hu, Jian Cao, Guandong Xu, Jie Wang, Zhiping Gu, and Longbing Cao, Cross-Domain Collaborative Filtering via Bilinear Multilevel Analysis, IJCAI'13, Proceedings of the Twenty-Third international joint conference on Artificial Intelligence, August 3-9, pp 2626-2632, Beijing, China, 2013.
Jian Cao, Jie Wang, Haiyan Zhao, and Minglu Li, An Event View Specification Approach for Supporting Service Process Collaboration, Concurrency and Computation: Practice and Experience, 25(13), pp1943-1966, 2013.
Xin Jin, Song Chen, Jie Wang, and Jinghua Xia, Investigation of Knowledge Management Maturity and Benchmarking Practices in Chinese Enterprises, PICMET ’13, San Jose, July 28 - August 1, 2013.
Jian Cao, Wenxing Xu, Liang Hu, Jie Wang, and Minglu Li, A Social-Aware Service Recommendation Approach for Mashup Creation (An Extended Paper), Int. J. Web Service Res, 10(1), pp53-72, 2013.
Jian Cao, Jie Wang, Haiyan Zhao, and Xiaohan Sun, A Service Process Optimization Method based on Model Refinement, The Journal of Supercomputing, 63(1), pp72-88, 2013.
Wenxing Xu, Jian Cao, Liang Hu, Jie Wang, and Minglu Li, A Social-Aware Service Recommendation Approach for Mashup Creation, IEEE 20th International Conference on Web Services, Santa Clara Marriott, CA, USA, June 27-July 2, 2013.
Shiyou Qian, Jian Cao, Yanmin Zhu, Minglu Li, and Jie Wang , H-Tree: An Efficient Index Structure for Event Matching in Publish/Subscribe Systems, IFIP/TC6 Networking, pp1-9, Brooklyn, New York, USA, May 22-24, 2013.
Dingyu Yanga, Jian Cao, Jiwen Fua, Jie Wang, and Jianmei Guo, A pattern fusion model for multi-step-ahead CPU load prediction, Journal of Systems and Software, Volume 86, Issue 5, pp1257–1266, May, 2013.
Jian Cao, Jie Wang, and Liang Hu, A Service Intermediary Agent Framework for Web Service Integration, The 2012 IEEE Asia-Pacific Services Computing Conference, pp14-21, Guilin, China, December 6-8, 2012.
Tianshu Chu, Jie Wang, and James O. Leckie , An Ontology-based Service Model For Smart Infrastructure Design, IEEE 2012 International Conference on Cloud and Service Computing (CSC), pp17-21, Shanghai, China, November 22-24, 2012.
Xiaogang Wang, Jian Cao, and Jie Wang, A Runtime Goal Conflict Resolution Strategy for the Agent, The 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, pp340-347, Macau, December 4-7, 2012.
Ling Wang, Yi-kai Juan, Jie Wang，Kai-meng Li, and Colin Ong, Fuzzy-QFD
Approach Based Decision Support Model for Licensor Selection, Journal of Expert Systems with Applications, 39(1): pp1484-1491, 2012.
Ling Wang, Zhan-Hong Zhu, and Jie Wang. ESM-Based National Innovation
Policy Influence Analysis with the Panel Data of Listed Chinese Electronic SMEs. PICMET‘11 (Technology Management in the Energy-Smart World), Portland, Oregon, pp293-299, July, 2011.
Yi-Kai Juan, Ling Wang, Jie Wang, and James Leckie, Decision Support System for Smart City Planning and Management , IBM Journal of Research and Development , Vol. 55 No. 1&2 Paper 3, January/March, 2011.
Jian Cao, Haiyan Zhao, Minglu Li, and Jie Wang, A Dynamically Self-configurable Service Process Engine, Journal of World Wide Web, (13), pp475-495, 2010.
Jian Cao and Jie Wang, Service Process Collaboration based on Event View Model, 2010 IEEE Asia-Pacific Services Computing Conference, 6-10 Dec. 2010, pp179-187, Hangzhou, China, 2010.
Kaimeng Li, Jie Wang, Ling Wang, Ryan Orr, and Yi-Kai Juan, A Hybrid Decision Support System for Efficient Planning and Management of Mega Projects, 2010 Engineering Project Organizations Conference, Sponsored by The Engineering Project Organization Society (EPOS), Stanford Sierra Conference Center, South Lake Tahoe, CA , USA, November 4-6, 2010.
Jian Cao and Jie Wang: Service Process Collaboration Based on Event View Model. The Proceedings of The 2010 IEEE Asia-Pacific Services Computing Conference, pp179-187, 2010.
Jian Cao, Jie Wang, Haiyan Zhao, and Xiaohan Sun, A service process optimization method based on model refinement, The Journal of Supercomputing (18 November 2010), pp1-17, doi:10.1007/s11227-010-0513-0.
Jian Cao, Haiyan Zhao, Minglu Li, and Jie Wang, A Dynamically Self-Configurable Service Process Engine, Journal of World Wide Web, 13(4):475-495， 2010.
Yi-Kai Juan, Gao Peng, and Jie Wang， A Hybrid Decision Support System for Sustainable Office Building Renovation and Energy Performance Improvement, Energy and Buildings, 42, pp290-297, 2010.
Jian Cao, Haiyan Zhao, Jie Wang, Shensheng Zhang, and Minglu Li: “Verifying Dynamic Workflow Change Based on Executable Path”, International Journal on Intelligent Control and Systems, Vol. 12, No.1, 37-44 2007.
Jian Cao, Jie Wang, Kincho Law, Shen-sheng Zhang, and Minglu Li: “An interactive service customization model”, Journal of Information & Software Technology 48(4): 280-296, 2006.
Jie Wang, James O. Leckie, Naveen Pai, and Jian Cao, “On Building Information and Knowledge Management Systems for Sustainable Development and Environmental Informatics”, Proceeding of the 4th International Conference on Environmental Informatics, Xiamen, China, 2005.
Jian Cao, Shensheng Zhang, Minglu Li, and Jie Wang, “Distributed Design Process Coordination based on A Service Event Notification Model”, Concurrent Engineering: Research and Application, Vol. 13(4), 2005.
Jian Cao, Jie Wang, and ShenSheng Zhang, “A Multi-agent Negotiation Based Service Composition Method for On-demand Service”, Proceeding of IEEE International Conference on Services Computing SCC 2005, July 11-15, Orlando, Florida, U.S.A, 329-332, 2005.
Yinglin Wang, Jie Wang, and ShenSheng Zhang, “Collaborative Knowledge Management by Integrating Knowledge Modeling and Workflow Modeling”, Lecture Notes in Computer Science, Vol. 3795, Proceeding of IEEE IRI 2005 (Knowledge Acquisition and Management), Las Vegas, Nevada, USA, 13-18, 2005.
Jian Cao, Yujie Mou, Jie Wang, Shensheng Zhang, and Minglu Li, “A Dynamic Grid Workflow Model Based On Workflow Component Reuse”, Proceeding of IEEE The 4th International Conference on Grid and Cooperative Computing, 424-429, 2005.
Jie Wang, James O. Leckie, Kincho H. Law and G. Wiederhold, 2004 “Distributed Information Organization and Management Framework for Regulation Compliance”, Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS 37), MiniTracks E-Government Cluster, 2004.
Jie Wang, Jian Cao, James O. Leckie, and Shensheng Zhang, “Managing E-Government IT Infrastructure: An Approach Combining Autonomic Computing and Awareness Based Collaboration”, Proceeding of IEEE CIT, 998-1003,2004.
Jian Cao, Jie Wang, Shensheng Zhang, and Minglu Li, “A Dynamically Reconfigurable System based on Workflow and Service Agents”, Engineering Application of Artificial Intelligence, Vol.17(7), 771-782, 2004.
Jian Cao, Jie Wang, Shensheng Zhang, Minglu Li, and Kincho Law, “Engineering Process Coordination based on A Service Event Notification Model”, IEEE GCC, 50-57, 2004.
Jian Cao, Shensheng Zhang, and Jie Wang, A Process Configuration Approach for Making-to-Order Enterprise, Proceeding of International Conference on Concurrent Engineering,162-172, 2004.
Jian Cao, Shensheng Zhang, Minglu Lia, and Jie Wang, “Verification of Dynamic Process Model Change to Support the Adaptive Workflow”, Proceedings-2004 IEEE International Conference on Services Computing, 255-261, 2004.
Wan-Chun Dou, Jie Wang, Xi-Ping Lie, Juan Sun and Shi-Jie Cai. “P2P-Based Knowledge Grid Oriented toward Cooperative Cognition”, KGGI 2004, in conjunction with 2004 IEEE/WIC International Conference on Web Intelligence/Intelligent Agent Technology, Beijing, 2004.
J. Peng and J. Wang, “On-demand Services Composition and Infrastructure Management”, Proceeding of IEEE The Second International Workshop on Grid and Cooperative Computing, Shanghai, 511-518, China, 2003.
J. Wang and P. K. Kitanidis, “Analysis of macro-dispersion through volume averaging: Comparison with stochastic theory”, Stochastic Environmental Research and Risk Assessment, 13(1/2), 66-84, 1999.