We are delighted to announce IEEE UCC 2016 will feature keynotes from the following distinguished guests.

743When Big Data Meets Cognitive Computing…on the Cloud

Hui Lei, Director and CTO, Watson Health Cloud IBM, IEEE Fellow

Abstract: The cloud has turned into an important platform for business innovation and industry transformation, leveraging the rapid growth of big data and the emerging paradigm of cognitive computing. Specifically, big data is becoming the world’s new natural resource and is driving fundamental changes in technology, business and society. With its exponentially increasing volume, velocity and variety, big data promises to be for the 21st century what steam power was for the 18th century, electricity for the 19th, and gas and oil for the 20th. At the same time, the rise of cognitive systems represents the dawn of a new era of computing. A necessary and natural evolution of traditional programmable systems, cognitive systems are able to scale and extend human knowledge, reason with purpose, and learn and improve over time. More importantly, cognitive computing is a key enabling technology for turning big data into insights and delivering on the full value of big data.In this talk, I will draw upon our experience at IBM building the Watson Health Cloud, and discuss how big data and cognitive computing can come together to enable innovative health solutions that tackle many of the clinical, societal, and economic issues faced by today’s health industry. I will present use cases, highlight the challenges, describe our approaches, and relate to client experiences as appropriate.

Biography: Dr. Hui Lei is CTO, Watson Health Cloud at IBM. An IBM Distinguished Engineer, he provides leadership on the Watson Health Cloud technical strategy, and spearheads the design and development of the Watson Health Cloud platform. Prior to his current role, Dr. Lei was Senior Manager, Cloud Platform Technologies at the IBM T. J. Watson Research Center, where he led IBM’s worldwide research strategies in cloud infrastructure services and cloud managed services. Dr. Lei’s technical vision and creative contributions have influenced many commercial software products and services, which range across big data solutions, cloud service offerings, middleware platform for mobile and pervasive computing, and e-business tooling. Dr. Lei is an active and recognized member of the international technical community. He is a Fellow of the IEEE, Editor-in-Chief of the IEEE Transactions on Cloud Computing, and Chair of the IEEE Computer Society Technical Committee on Business Informatics and Systems. He has taken part in many international conferences as a steering committee chair, general chair, technical program chair, or keynote speaker. He is also a prolific inventor and has over 70 patents to his credit. He received his PhD in Computer Science from Columbia University.

Performpicance Modeling and Optimization in Mobile Cloud Computing Environment

Dr. Jiannong Cao, Hong Kong Polytechnic University, Hung Hom, Hong Kong, IEEE Fellow

Abstract: Mobile cloud computing has emerged as a new paradigm in IT industry and led to many research and development initiatives. High performance for both the end users and system providers remains to be an essential goal but is much more difficult to achieve in the new paradigm. Due to the diversity of applications in mobile cloud computing, there exists different performance models and thus various methodologies to enhance the application performance. In this talk, we focus on three types of mobile cloud applications, i.e., the workflow applications, data streaming applications, and the content delivery applications, and discuss how to model the performance of the applications. Based on the performance models, we then present our methods to optimize the application performance. In particular, for the workflow and data streaming applications, we will present a series of new solutions on computation partitioning to optimize the application performance, while for the content delivery application, we will present our recent work on load dispatching and service placement to minimize the overall latency of end users in accessing the content/services.

Biography: Dr. Cao is currently a chair professor and head of the Department of Computing at Hong Kong Polytechnic University, Hung Hom, Hong Kong. His research interests include parallel and distributed computing, computer networks, mobile and pervasive computing, fault tolerance, and middleware. He has co-authored 3 books, co-edited 9 books, and published over 300 papers in major international journals and conference proceedings. He is a fellow of IEEE, a senior member of China Computer Federation, and a member of ACM.  He was the Chair of the Technical Committee on Distributed Computing of IEEE Computer Society from 2012 – 2014.  Dr. Cao has served as an associate editor and a member of the editorial boards of many international journals, including ACM Transactions on Sensor Networks, IEEE Transacitons on Computers, IEEE Transactions on Parallel and Distributed Systems, IEEE Networks, Pervasive and Mobile Computing Journal, and Peer-to-Peer Networking and Applications. He has also served as a chair and member of organizing / program committees for many international conferences, including PERCOM, INFOCOM, ICDCS, IPDPS, ICPP, RTSS, DSN, ICNP, SRDS, MASS, PRDC, ICC, GLOBECOM, and WCNC. Dr. Cao received the BSc degree in computer science from Nanjing University, Nanjing, China, and the MSc and the Ph.D degrees in computer science from Washington State University, Pullman, WA, USA.

picPlatform Development for Collaborative Computing with Urban Big data

Professor Minyi Guo, Chair of the Department of Computer Science and Engineering, Shanghai Jiao Tong University

Abstract: Nowadays, sensing technologies and large-scale computing infrastructures have produced a variety of big data in urban spaces, e.g. human mobility, air quality, traffic patterns, and geographical data. The big data implies rich knowledge about a city and can help tackle these challenges when used correctly. We believe this is the right time to research on holistic urban big data which has been made possible due to recent advances in communication technologies that allow wireless connection and untethered data exchange among vast urban sensing and computing devices, as well as advanced data and computing science that provides us necessary methods and computing power to understand, model, and reason the urban data and people. In this talk, we give some properties for processing urban big data, introduce a system for urban big data processing, and discuss how the collaborative computing bridges the data and computation in the cyber space and the environment, systems, people and things in the physical world.

Biography: Minyi Guo is currently Zhiyuan Chair professor and chair of the Department of Computer Science and Engineering, Shanghai Jiao Tong University (SJTU), China. Before joined SJTU, Dr. Guo had been a professor of the school of computer science and engineering, University of Aizu, Japan. Dr. Guo received the national science fund for distinguished young scholars from NSFC in 2007, and was supported by “1000 recruitment program of China” in 2010. His present research interests include parallel/distributed computing, compiler optimizations, embedded systems, pervasive computing, and cloud computing. He has more than 300 publications in major journals and international conferences in these areas, including the IEEE Transactions on Parallel and Distributed Systems, the IEEE Transactions on Computers, the ACM Transactions on Autonomous and Adaptive Systems, INFOCOM, IPDPS, ICS, ISCA, HPCA, SC, WWW, PODC, etc. He received 5 best paper awards from international conferences. He is on the editorial board of IEEE Transactions on Parallel and Distributed Systems and Journal of Parallel and Distributed Computing.

picturewCan the Bright Cloud be a Business Model?

Professor Jae Kyu Lee (KAIST, Carnegie Mellon University and Xian Jiaotong University)

Abstract: The Bright Internet aims a safer Internet platform where the origination of malicious behaviors can be deterred because their origins can be identified. As such, the primary goal of the Bright Internet is the establishment of Preventive Security paradigm in contrast with the current paradigm of protective security of its own system. The current cloud computing service providers have no choice but to adopt the protective security paradigm. In this talk, the benefit of adopting the Bright Internet platform will be presented in the cloud service provisioning. A question is how to motivate the individual Cloud Service Providers (CSPs) to adopt the Bright Internet platform. For this purposes, we analyze the benefits of adopting the Bright Internet platform in terms of marketing, economy, and compliance to regulation.

  • Marketing Advantage: Suppose that the Bright Internet Global Governance Center certifies the cleanness level of outgoing messages which will upgrade their trustworthiness to their online business partners. If the clients of a CSP need such trustworthiness for their business creation, then the CSP needs to offer the Bright Internet based cloud services.
  • Economic Advantage: Suppose the Bright Internet Global Governance Center evaluates the levels of harms created by the originating companies such as CPSs. If the cost of preventive measure is more economical than the payment for the penalty, CSPs will be motivated to invest for preventive security for their clients.
  • Compliance Advantage: If the social value of preventive security is bigger than the sum of individual investments for it, the legislation that requires the preventive security measures will be socially justified. Then the CSPs will have a good reason to adopt the preventive measures like the Bright Internet.

We present the architecture of Bright Cloud that justifies these business models. To explain the concept of Bright Cloud, this talk will explain the three goals of Bright Internet (Preventive Security, Freedom of Anonymous Expression for the Innocent Netizens, and Privacy Protection) and Five Basic Principles (Origin Responsibility, Deliverer Responsibility, Identifiable Anonymity, Global Collaborative Search, and Privacy Protection). The specific Bright Cloud business models may adopt the essential principles that are most suitable for the specific business strategy.  The first mover of Bright Cloud will be able to get the benefit of marketing advantage, and eventually the benefits of economic and compliance advantages.

Biography: Jae Kyu Lee was the HHI Chair Professor of Korea Advanced Institute of Science and Technology, and has become Professor Emeritus of KAIST since September 2016. He is currently the Director Emeritus of Bright Internet Research Center at KAIST, a Distinguished Visiting Professor at Heinz College of Carnegie Mellon University, and the Honorary Yingluo Wang Professor at School of Management at Xian Jiaotong University in China as a co-director of the Bright Internet Global Governance Research Center, China. He is the Immediate Past President and Fellow of Association for Information Systems, and conference chair of International Conference on Information Systems 2017 in Seoul. He is also the chair of inaugurating Bright Internet Global Summit that will be held in Seoul as the pre-ICIS 2017. He received a Ph.D. in Operations and Information Systems from the Wharton School, University of Pennsylvania (1985), and has been a Professor of Information Systems and Electronic Commerce at KAIST since then. He was the founding editor-in-chief of the journal, Electronic Commerce Research and Applications (Elsevier, SSCI and SCIE Accredited), and was the founding chair of the International Conference on Electronic Commerce. He was a chair of the International Conference on Electronic Commerce (ICEC 1998, and ICEC 2000) and Pacific Asia Conference on Information Systems (2001, 2006). He was the President of Korea Society of Management Information Systems and Korea Society of Intelligent Information Systems, and served for the program committee of numerous international conferences in information systems, intelligent systems, and e-commerce. He authored four English books and seven Korean books with many editions in the area of Electronic Commerce, Information System, and Intelligent Systems, including Electronic Commerce: A Managerial Perspective (2014 Springer; coauthored with Efraim Turban), Artificial Intelligence in Finance and Investing (Irwin). He published many international journal papers in journals such as MIS Quarterly, Information Systems Research, Decision Support Systems, Communications of ACM, Management Science, International Journal of Electronic Commerce, Expert System with Applications, European Journal of Information Systems, and many others. He presented many keynote speeches at ICIS, PACIS, AMCIS, and ICEC. He received the best paper awards ten times from the major conferences, and received a national decoration from the Korea Government for his contribution to the development of the IT industry. His research interest has been the application of Artificial Intelligence for Managerial Decision Support, Electronic Commerce, and Green IT, and his current research interest is the establishment of the Bright Internet platform. He has conducted 45 granted projects on the topics of the Bright Internet, Green Business, eCommerce strategies for financial sectors, SCM and eProcurement Systems, case based project management systems, intelligent scheduling systems for ship building, power generation, and refinery.

dharmaThe Art of Transforming Traditional Utilities to the Cloud Model

Dharma Rajan, Solution Architect Leader, Network Function Virtualization, VMware USA

Abstract: Public, private, and hybrid clouds are now a de facto industry model. New cloud services are being introduced by the industry at a very fast pace. This keynote session will take you through the journey of cloud evolution, from enterprise to utilities, and the industry transformation that is happening. We will drive through telco cloud with the advent of SDN and NFV, as well as look at how 5G and IoT cloud evolution will enable new service models. An artful transformation to software-defined smart cities with smart utilities operated from the cloud is becoming close to reality. With trends in automation, orchestration, and evolving technology like multi-cloud micro-services, Mobile Virtual Network Operators can offer new revenue generating cloud services that might transform the way we do business and research.

Biography: Dharma Rajan is a leading expert in cloud technology working as lead Solution Architect at VMware, USA. His areas of expertise span infrastructure virtualization, hybrid cloud, NFV, and cloud security. Prior to joining VMware, Dharma has worked at Ericsson, USA for over a decade, building 4G platform architectures, carrier grade networks, and network management systems. He has also worked at Cisco Systems, USA on enterprise architecture. He has several technical publications and is an invited speaker at major industry events and world conferences. He holds an MS in Computer Engineering from NCSU, USA and M.Tech in CAD from IIT-Kanpur, India.

minCloud-Assisted and Data-Driven Knowledge Discovery for Future Internet

Prof. Geyong Min, Chair in High Performance Computing and Networking, University of Exeter, UK

Abstract: Autonomic Future Internet (AFI) coupled with the emerging SDN/NFV technologies is regarded as a promising and viable solution for addressing many grand challenges faced by future 5G networks and Cloud computing systems. The ambition of AFI is to exploit an autonomic, intelligent and self-managing Future Internet with consequent improvement in system efficiency and performance, increased profitability, and reduced OPEX and CAPEX. Two key features of AFI are self-management and cognitive learning; the former is essential for complexity reduction and fast adaptation to changing situations and the latter can increase the intelligence through flexible knowledge utilization. In this talk, we will present state-of-the-art network architecture for AFI that is seamlessly integrated with SDN and NFV. The core Knowledge Plane within this unified architecture is responsible for real-time network big data analysis and knowledge discovery in order to maintain high-level behaviors of how the system should be configured, managed, and optimized. To establish a powerful, flexible and scalable Knowledge Plane in AFI, we will present the innovative big data processing technologies and cost-effective platform developed in Cloud-assisted computational framework. This framework includes the unified representation of heterogeneous big data and real-time incremental data analysis tools for extracting valuable insights to support better decision making for system design, resource management and optimization. This talk offers the theoretical underpinning for efficient processing of big data, and also opens up a new horizon of research and development by exploiting the key intelligence and insights hidden in rich network big data for design and improvement of Future Internet and Cloud computing systems.

Biography: Professor Geyong Min is a Chair in High Performance Computing and Networking with the Computer Science discipline in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, UK. His recent research has been supported by European FP6/FP7, UK EPSRC, Royal Academy of Engineering, Royal Society, and industrial partners including Motorola, IBM, Huawei Technologies, INMARSAT, and InforSense Ltd. Prof. Min is the Co-ordinator of two recently funded FP7 projects: 1) Quality-of-Experience Improvement for Mobile Multimedia across Heterogeneous Wireless Networks; and 2) Cross-Layer Investigation and Integration of Computing and Networking Aspects of Mobile Social Networks. As a key team member and participant, he has made significant contributions to several EU funded research projects on Future Generation Internet. He has published more than 200 research papers in leading international journals including IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Multimedia, IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems, and at reputable international conferences, such as SIGCOMM-IMC, ICDCS, IPDPS, GLOBECOM, and ICC. He is an Associated Editor of several international journals, e.g., IEEE Transactions on Computers. He served as the General Chair/Program Chair of a number of international conferences in the area of Information and Communications Technologies.

picPaperbook: Design and Implementation

Prof Xinbing Wang, Shanghai Jiaotong University

Abstract: In this keynote, we will introduce a novel academic system, paperbook or AceMap, to analyze the big scholarly data and present the results through a “map” approach. AceMap integrates several algorithms in the eld of network analysis and data mining, and then displays the information in a clear and intuitive way, aiming to help the researchers facilitate their work. After describing the big picture, we present achieved results and our work in progress. By far, AceMap has implemented the following functions: dynamic citation network display, paper clustering, academic genealogy, author and conference homepage, etc. We have also designed and performed distributed network analysis algorithms in a cutting-edge Spark system and utilized modern visualization tools to present the results. Finally, we conclude my keynote by proposing the future outlooks.

Biography: Professor Xinbing Wang received the B.S. degree (with hons.) in Automation from Shanghai Jiao Tong University, Shanghai, China, in 1998, the M.S. degree in computer science and technology from Tsinghua University, Beijing, China, in 2001, and the Ph.D. degree with a major in electrical and computer engineering and minor in mathematics from North Carolina State University, Raleigh, in 2006. Currently, he is a Professor in the Department of Electronic Engineering, and Department of Computer Science, Shanghai Jiao Tong University, Shanghai, China. Dr. Wang has been an Associate Editor for IEEE/ACM Transactions on Networking, IEEE Transactions on Mobile Computing, and ACM Transactions on Sensor Networks. He has also been the Technical Program Committees of several conferences including ACM MobiCom 2012,2014, ACM MobiHoc 2012-2017, IEEE INFOCOM 2009-2017.

sonThe Use of Machine Learning in Business

Sonya Zhang, California State Polytechnic University, U.S.

Abstract: Machine Learning is no doubt gaining momentum and reaching the top of Gartner’s hype curve. As data analytics becomes a more common practice, businesses are now looking deeper into their data to increase efficiency and competitiveness using machine learning, which can learn from data, find hidden insights, and make predictions without being explicitly programmed. Today Machine learning can be found in many business applications, ranging from facial and object recognition, fraud detection, product or content recommendation, to effective web search and targeted ads. In this talk I will give a brief introduction on machine learning, and then focus on current applications and examples of machine learning in different business functions, business models, and industries, and finally, the opportunities and challenges.

Biography: Sonya Zhang is an Associate Professor of Computer Information Systems at the College of Business Administration, California State Polytechnic University, Pomona. She received her PhD in Information Systems and Technology from Claremont Graduate University. She also holds an M.S. in Computer Science, and an MBA from Illinois State University. Sonya’s research specialties are: Web and Software Development, Digital Analytics, Internet Entrepreneurship, and Online Learning. She co-authored The Smarter Startup: A Better Approach to Online Business for Entrepreneurs. Her work also appeared in Journal of Computer Information Systems, ACM Interactions, Journal of Information Systems Education, Journal of Information Technology Education, International Journal of Healthcare Information Systems and Informatics, HICSS, AMCIS and IEEE conference proceedings. Prior to joining academia, Sonya was a software engineer in health informatics and higher education for seven years, worked on ERP, Business Intelligence, CMS, eLearning and eHealth products/projects

yangBig Earth Data – a New Dimension for Digital Earth

Professor Yong Xue, University of Derby, U.K

Abstract: Digital Earth is a multi-resolution, three-dimensional representation of the planet, into which we can embed vast quantities of geo-referenced data (Al Gore, 1998). As a new dimension of the Digital Earth, in addition to Computational Science, Mass Storage, Satellite Imagery, Broadband networks, Interoperability and Metadata, Big Data technologies provide a set of advanced tools that can improve development of Digital Earth. After a period of slow but steady scientific progress, this scientific area seems to be mature for new research and application breakthroughs. The rapid progress in the development of integrated Big Data and Earth observation tools has boosted this process (Goodchild et al. 2012, Guo et al. 2016). As one of the Big Data fields, Earth observation Big Data is unleashing an interesting time of transition, driving the innovation and development of disciplines, becoming a new key to the cognition of nature and a new engine for Earth sciences. Based on widely collected Earth observation big data combined with models of the Earth system, the development of theory and methods for knowledge discovery related to big Earth data is an important scientific issue needing attention.

Biography: Professor Dr. Yong Xue (senior member of IEEE) is a Professor in Computation in University of Derby, United Kingdom. He received his BSc degree in Physics and his MSc degree in remote sensing and GIS from Peking University, China in 1986 and 1989, respectively. He received his PhD in remote sensing and GIS from University of Dundee, UK in 1995. His main research interests include Geocomputation, aerosol optical depth retrieval from remotely sensed data, thermal inertia modeling and heat exchange calculation for the boundary layer. Prof. Xue has published over 104 peer-reviewed journal papers (with the highest Impact Factor at 7.885) and over 148 peer-reviewed conference papers. The overall citations of his publications are over 1330 times with one paper citations of over 130 times (Google Scholar). He has served as the technical programme committee members for several international conferences, such as IEEE/IGARSS conferences and the International Conferences on Computational Science (ICCS). Professor Xue is an Associate Editor of the International Journal of Remote Sensing published by Taylor and Francis, UK, a Chartered Physicist and a member of the Institute of Physics, UK, and the Chapter chair of the joint chapter of IEEE Aerospace Engineering Society/Oceanic Engineering Society/Geosciences and Remote Sensing Society since 2004 in United Kingdom. Contact him at: y.xue@derby.ac.uk.

thMeeting Society Challenges: Big Data Driven Approaches

Dr. Liangxiu Han, Manchester Metropolitan University, U.K

Abstract: This talk will be focusing on new developments and methods based on big data driven approaches to address society challenges and their applications into application domains such as Health, Food, Smart Cities.

Biography: Dr. Liangxiu Han is a Reader in Computer Science, where she is a Deputy Director for two centres: Informatics Research Centre and the Man Met Crime and Well-Being Big Data Centre. Having worked in both industry and academia, Dr. Han has over 14 years research and practical experiences in developing intelligent ICTenabled software solutions for large scale data processing and data analysis and mining in different application domains (e.g. Health, Smart Cities, Bioscience, Cyber Security, Energy, etc.) using various datasets including images, sensor data, and web pages (funded by innovate UK, EPSRC, EU-FP7, Government and Industry respectively). As a Principal Investigator (PI) or Co-PI, Han has been conducting research in relation to large-scale data processing, data mining, cloud computing, software architecture (funded by EPSRC, BBSRC, Innovate UK, Horizon 2020, Industry, Charity, respectively, etc.). Dr. Han is a member of EPSRC Peer Review College, an independent expert for Horizon 2020 proposal evaluation/review and British Council Peer Review Panel. She is also a reviewer for IEEE computer society and Journal of Parallel and Distributed Computing, Journal of Information Science from Elsevier science, IEEE Transaction on Service Computing, Brain Computing, IEEE Transaction on Biomedical Imaging engineering, Bioinformatics, Brain Informatics, Clustering Computing, etc. and various international conferences and programme committee member of various International Conferences. She had been also involved in number of professional activities in UK and China.