David G. Belanger, PhD, Senior Research Fellow, Stevens Institute of Technology, New Jersey, USA Topic: Big Data - The Next Phase Abstract

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1 David G. Belanger, PhD, Senior Research Fellow, Stevens Institute of Technology, New Jersey, USA Dr. David Belanger is currently a Senior Research Fellow at Stevens Institute of Technology. In this role he continues his work in Big Data Technology, Applications, and Governance. He also teaches and helps lead in the Business Intelligence & Analysis Master Degree program and the Center for Big Data Innovation. In addition, he is involved in consulting related to Big Data in areas such as Health Care, security, and Networking. He was Chief Scientist of AT&T Labs, and Vice President: Information, Software, & Systems Research at AT&T Labs, and creator of the AT&T InfoLab, an early participant in Big Data research and practice. Dave joined Bell Laboratories in He has led research in software systems and engineering, information mining, information visualization, and development in very large scale data systems. He built the Software Engineering Research Department which provided software tools and techniques used across AT&T Bell Labs, and via open source, across the world. Prior to AT&T, Dave was associate professor of Mathematics and Computer Science at University of South Alabama, and co-founder of Gulf Coast Data Systems (a computing services company). He received his B. S. from Union College (NY) in Mathematics, and an M. S. & Ph.D., in Mathematics, from Case Western Reserve University. In 1998, Dave was awarded the AT&T Science and Technology Medal for contributions in very large scale information mining technology. In 2006, he was named an AT&T Fellow for lifetime contributions in software, software tools, and information mining. Dr. Belanger received the 2009 IEEE Communications Society Industrial Innovator Award. Topic: Big Data - The Next Phase We have been in the realm of Big Data for more than a decade, and have seen a large number of common and valuable application types. These are increasingly supported by widely available tools, both commercial and open source, so that the advantages of Big Data are starting to become accessible to a much wider audience. At the same time, new sources of data and types of applications are ready to dominate the Big Data arena. Many of these are concerned with data generated by devices, rather than individuals, and require applications that are real time, or even predictive. The toolsets are also evolving to satisfy the needs of these applications. In this talk, we look at where we are going. Dan Holle, Chief Technology Officer of Data Platforms, Greenplum, a division of EMC Dan Holle is the CTO of Data Platforms at Greenplum, a division of EMC. Recognized as a pioneer in parallel processing, databases and analytics, Mr. Holle is co-creator of the SQL language, and holds patents in data mining, semantic search, indexing and data profiling. He has extensive experience as a technology industry leader, was one of the founding engineers at Teradata, and has launched several start-up companies related to database management products and services in the data warehousing and big data analytics field. xxvi

2 Topic: Big Data Requires a New Platform for a New Era of Analytics: The Way to Win with Data, Apps and Analytics. Modern Internet greats leverage the consumer-grade enterprise to generate immense new business value. Startups churn out new, market-changing products and services. Even individuals around the world use it to create extraordinary impact. The consumer-grade enterprise is a convergence of new technologies, and it has enabled the rapid development of a new class of applications, data-driven and context intelligent. They are quickly changing everything about how we live and work. But established companies have been largely left out. Achieving this capability alongside entrenched technologies and existing data platforms has been stunningly difficult. Big Data fabrics enable Enterprises to become consumer grade and for the first time, the employees of the enterprise have the capabilities necessary to rapidly create consumer-grade applications. To create powerful experiences that serve a consumer in the context of who they are, where they are, and what they are doing in the moment. To store, manage and deliver value from fast, massive data sets. To build, deploy and scale at an unprecedented pace. Learn how Big Data platforms enable the integration of these sophisticated new data fabrics with modern programming frameworks and cloud independence. Mark Cusack, Chief Architect, RainStor Mark joined RainStor in 2004, and is a founding developer. He was formerly a senior scientist and team lead at QinetiQ, where he researched distributed simulation techniques, and developed physics-based models of human behaviour to support military training and operations. He also led government and industry projects in the areas of grid and pervasive computing. Before joining QinetiQ, Mark worked in academia, where he combined cluster computing methods with quantum mechanics to predict the properties of semiconductor microstructures. Mark holds a Masters in Computing and a PhD in Physics from Newcastle University. Topic: Data Integrity, Privacy and Trust Issues in Hadoop : Hadoop excels as a scalable compute and storage platform. However, it falls short with respect to security and compliance. How do you keep track of sensitive data, and how can you manage its lifecycle? How do you find out who s accessed it? And how can you protect it from being tampered with? These questions become financially and reputationally significant when the data stored includes sensitive data, for example credit cardholder details and other personally identifiable information. In this talk we critically examine Hadoop in the light of key regulatory requirements. We identify gaps in Hadoop s current security model, and discuss the features and technologies needed to support secure and compliant Hadoop applications moving forwards. xxvii

3 Dr. Hua-Ping (Kevin) Zhang, Professor of Beijing Institute of Technology & Collaborated Scientist with Comrise, USA Dr. Hua-Ping (Kevin) Zhang is an Associate Professor of Beijing Institute of Technology(BIT), as well as the Director of Department of Web Search, Mining and Security. In addition, Dr. Zhang is an advanced member of China Computer Federation, and Guest Professor and Lecturer at Capital Normal University and Liaoning Normal University in China. Dr. Zhang is also a reviewer of several publications and journals, such as Computer Research and Development, and China Online Scientific Paper. In terms of research, his primary focuses have been Micro-blog Computing, Natural Language Processing, Information Retrieval and Recurity, and Big Data Search and Mining. Overall, Dr. Zhang and his team have been granted over 10 research projects by various government associations, such as the National Science Foundation, National High-Tech Research and Development Program of China, and the National Basic Research Program of China. Finally, Dr. Zhang has published 3 books and 20+ papers throughout the course of his career, as well as developed Chinese lexical analysis system ICTCLAS, which ranked 1st in the International Chinese Word Segmentation Bakeoff. Consequently, Dr. Zhang was awarded the first prize of Qian Wei-Chang Chinese Information Science and Technology Award, the President Scholarship of Chinese Academy of Sciences (CAS), and the Special President Award of Institute of Computing Technology (ICT), CAS. Topic: Big Data Mining on Weibo from a Macro, Micro and Content Perspective With the rapid development of social networks, Weibo in China has been widely adopted by over 300 million users, reaching a utilization ratio of 50% in 2012, and providing a medium for users to share their opinion and sentiment on different topics and trends. This talk will review a macro-statistical survey that was conducted across 17+ million Weibo users profile, as well as present personality and activity modeling for each of the profiles that was produced through the web crawling and mining of Big Data. Nicholas Zhang, Principal Researcher and Leader of HCI & SYS Group in Noah Ark Lab, Huawei Nicholas Zhang has over 16 years research and system development experience in network, distributed system and communication system architectures. He has contributed to more than 90 patents. He had been a product development team leader of smart devices in 2002 to pioneer new consumer business for Huawei. He then started to lead the research on future Internet and cooperative communication in In 2009, he became in charge of the advance network technology research department, leading research on future network, distributed computing, database system, and data analysis. His recent research focuses on Human Machine Interaction and Systems in data analysis and intelligence system. xxviii

4 Topic: Next Generation Intelligent Phone: Hope or Hype? With the development of the Mobile Internet, smart phone is becoming more and more popular. Will the future phone become smarter close enough to Human intelligence or beyond the human s ability? That will be the biggest challenge in the future. At first, we have been getting more and more data and more semantic data in mobile area than before and other areas, giving us the chance to well understand in deep and use the data properly. Secondly, new approaches enable us to discover the data in the Cloud computing and distributed computing. Finally, there will be more and more devices connected by mobile as bridge that will provide the fundamental foundation for intelligence. We are addressing the above research challenges in attempt to develop a new phone called intelligence phone (NGIPHONE), and we hope that it will be new trends in next 10 years. In this talk, the smart phone intelligence will be addressed from three aspects: (i) Human factor in machine learning, (ii) Mobile intelligence, and (iii) Future research challenges and directions. Bin Xie, PhD, Founder & President, InfoBeyond Technology LLC, USA Dr. Bin Xie received his M.Sc and Ph.D. degrees in Computer Science and Computer Engineering from the University of Louisville, Kentucky, USA, 2003 and 2006 respectively. His book tiltled Handbook/Encyclopedia of Ad Hoc and Ubiquitous Computing (World Scientific: ISBN-10: X) is one of the bestselling handbooks at World Scientific Publisher. Dr. Xie is also the author of books: Handbook of Applications and Services for Mobile Systems (Auerbach Publication, Taylor and Francis Group, ISBN: , 2012) and Heterogeneous Wireless Networks- Networking Protocol to Security (VDM Publishing House: ISBN: , 2007). He has published 70+ papers in the IEEE conferences, magazines, official governmental reports, and journals. Some of papers have appeared in the most-cited journals in the areas of Telecommunication and Computer Architecture. His research interests are focused on cyber security, network management, wireless communication, and user performance. In particular, he has performed substantial research works on the fundamental aspects of network deployment, intrusion detection, performance evaluation, and Internet/wireless infrastructure security. He also studied many issues of coding theory, information process, Quality of Service (QoS), clustering, and image reconstruction. Dr. Xie is the founder of InfoBeyond Technology LLC and current is the president of the InfoBeyond. InfoBeyond has delivered advanced solutions for wireless mobile ad hoc communications, network security, information process, and data protection in support of unique needs of our customers, maintaining a stable increase of business in the past few years. Dr. Xie is an IEEE senior member. He is an editor member of the Journal of International Journal of Information Technology, Communications and Convergence (IJITCC). He is the Guest edit chair of several journal special issues. Dr. Xie was invited as the program chair or TPC member of a number of international conferences. Topic: Learning Social Kernel Communities and Behaviors from Big Social Media In the past decade, we have seen the increasingly flourishing of social median such as Twitter, Facebook, Google+, and MySpace. The social networks have all grown up to the top sites globally in terms of the global network traffic. The big data of social media imposes many challenges for us to (i) track the communities, (ii) learn the social interactions of interests, and (iii) predict the social behaviors if necessary. Current approaches are very limited to provide reliable and valid understanding of the meanings that are otherwise never discovered from the data sets we collected. In this talk, we will further explore the technical challenges, review the existing approaches, and particularly present an insight on the xxix

5 semantic understanding of the social media such that the time and geographic properties of the social interactions are precisely revealed. xxx

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