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Keynote Speakers
 
Keynote Speaker 1: Cloud-Assisted Mobile Computing and Pervasive Services
Prof. Min Chen
School of Computer Science and Technology
Huazhong University of Science and Technology, China
 
Biography: 
Dr. Min Chen is a professor in the School of Computer Science and Technology at Huazhong University of Science and Technology (HUST). He was an assistant professor in the School of Computer Science and Engineering at the Seoul National University (SNU) from Sep. 2009 to Feb. 2012. He was the R&D director at Confederal Network Inc. from 2008 to 2009. He worked as a Post-Doctoral Fellow in Department of Electrical and Computer Engineering at University of British Columbia (UBC) for three years. Before joining UBC, he was a Post-Doctoral Fellow at SNU for one and half years. He received Best Paper Award from IEEE ICC 2012, and Best Paper Runner-up Award from QShine 2008. He has more than 180 paper publications. He serves as editor or associate editor for Wireless Communications and Mobile Computing, IET Communications, IET Networks, Wiley I. J. of Security and Communication Networks, Journal of Internet Technology, KSII Trans. Internet and Information Systems, International Journal of Sensor Networks. He is managing editor for IJAACS and IJART. He is Co-Chair of IEEE ICC 2012-Communications Theory Symposium, and Co-Chair of IEEE ICC 2013-Wireless Networks Symposium. He is General Co-Chair for the 12th IEEE International Conference on Computer and Information Technology (IEEE CIT-2012). His research focuses on multimedia and communications, such as multimedia transmission over wireless network, wireless sensor networks, body sensor networks, RFID, ubiquitous computing, intelligent mobile agent, pervasive computing and networks, E-healthcare, medical application, machine to machine communications and Internet of Things, etc. He is an IEEE Senior Member since 2009.
Summary:
Advances in mobile communication networks and increasing deployments of mobile smart devices have brought rich mobile experiences to end users. However, further improvement of service quality and large deployment of mobile pervasive services are hampered by resource constraints of mobile devices and bandwidth limitations of wireless networks. Recently, mobile cloud computing is emerging rapidly as an exciting new paradigm to extend the capabilities of mobile devices and platforms, which, in turn, are changing the industrial production and people's daily life. Developments of innovative pervasive mobile services, e.g., mobile video streaming, rich media dissemination, surveillance, e-gaming, e-health care, etc., can be greatly facilitated by mobile cloud computing platforms employing emerged and emerging technologies. This talk is to introduce some recent issues and applications related to cloud-assisted mobile computing and pervasive services.
 
Keynote Speaker 2: Device Age: How technology is impacting our lives today and in future
 
Alok Srivastava
CTO, ISV Practice, Microsoft Corporation, USA
Biography:
Alok Srivastava is working as CTO for ISV practice at Microsoft Corporation. As CTO, he is responsible for working with Microsoft partners to help them design and architect their products for scale performance while taking advantage of emerging technology trends. As ISV CTO he makes sure that ISV consulting team is ready to tackle emerging technologies before they become main stream. Keeping track of technical evolutions, assessing its impact on current partner products and guiding ISV business team to be ready for business impacts is also part of his responsibilities. Before becoming CTO, Alok worked as technology and business advisor to a number of Microsoft ISV partners enabling them to bring successful products to their respective markets. Alok has worked with advance technology companies building future medical device, medical information management systems, hospital management systems, POS solutions, insurance processing solutions, trade management systems, security software providers and many others.
Prior to joining Microsoft, Alok worked for Sybase and Oracle Corporation, leading product development and R&D teams. His played a key role in distributed replication management systems, database extensibility, multi-media management in relational databases, location based services, formalization of web services, service-oriented architecture and collaboration platform. Alok worked as CTO with his startup focusing on sales process optimization and automation.
Alok’s research interest include distributed high performance computing, cloud computing, service oriented architectures, complex high scale systems, data architecture and business intelligence. He has worked on some key research projects related to web services and internet computing which has resulted in a number of patents that have been granted or are being processed.
Summary:
Use of devices and sensors is growing in every aspect of our lives and how we interact with them is changing at the same pace. Continuous growth in Cloud computing and its adoption in mainstream businesses is fueling the fire. We are entering an age of computing where change and adoption to these changes is a part of life. Next generation of users are expecting much more than our generation ever did. All the guiding principles that we have grown used to in the past are not guiding the use of technology for generation X. In just a few short years, we have gone from keyboard and mouse to touch and gesture. The pace of change is faster than ever before. This keynote is a journey through time with a close look at how we are likely to work with devices in near future. We will take a historical look at how we have progressed over past many years. We will examine facts that are driving this change now and we will take a glimpse into what our future may look like.
 
 
Keynote Speaker 3: Moving Beyond Big Data: Picking the needles of insight from the data haystack using Big Analytics
 
George Kong
Director of the Consulting and Professional Service, Teradata
Biography:
George Kong is the Director of Consulting and Professional Services in the Teradata’s Aster Data Center of Innovation.  George brings over 9 years of professional experience in the software industry, where he has successfully transformed several groups into high-achieving teams.  George manages a team of consultants and analytic scientists who enable customers gain valuable insight from their data.
Prior to Teradata’s purchase, George ran professional services, customer service, and customer training in Aster Data.  Prior to taking on this role, George has led the deployment and value realization of some of the largest analytic platforms in the world, including multiple 100+ terabyte systems at Myspace, LinkedIn, and Barnes & Noble as an Aster Data lead consultant.  George was also a key member of the Aster engineering team where he designed and implemented some of the features of the Aster nCluster product.
Prior to joining Aster Data, George was the founder and CEO of Proximoso, a location-based social networking startup.  Prior to Proximoso, George was a Senior Engineer working in NetApp’s storage group.George holds a M.S. in Computer Science from Brown University and an MBA from the Haas School of Business at U.C. Berkeley.
Summary:
In many Big Data discussions, the volume of data and the technology to store and manage it efficiently takes center stage.  The more important question should be, “How do I most efficiently harness my data to get value and insight from it that can help drive the business forward?”  To do that, you will need analytic toolsets that your team can set up, ingest various types of data, and perform different kind of analysis on them quickly and easily.  We will explore what you should pay attention to when choosing your toolset to leverage big data, and how to allow your team to start driving business insight from the data instead of just managing them.
 
Keynote Speaker 4: Big Data: Opportunities and Challenges
 
Prof. Adel S. Elmaghraby
Department Chair

Director Innovative and Emerging Technologies Lab
University of Louisville
 
 
Biography:  

Adel S. Elmaghraby is Professor and Chair of the Computer Engineering and Computer Science Department at the University of Louisville. He has also held appointments at the Software Engineering Institute -Carnegie-Mellon University, and the University of Wisconsin-Madison. He advised over 60 master's graduates and 20 doctoral graduates. His research contributions and consulting spans the areas of Intelligent Multimedia Systems, Neural Networks, PDCS, Visualization, and Simulation. His Research applications include medical Imaging, Bioinformatics, and Computer-Aided Diagnostics. He is a well-published author (over 200 publications), a public speaker, member of editorial boards, and technical reviewer. He has been recognized for his achievements by several professional organizations including a Golden Core Membership Award by the IEEE member of the Engineering in Medicine and Biology Society, the Computer Society, and Computational Intelligence Society. Dr. Elmaghraby continued collaborations, mentoring, and scientific contributions have resulted in published articles in many prestigious journals such as IEEE-TMI, Medical Physics, Journal of Neuroscience Methods, and Protein Engineering. He is also an active member of the IEEE-CS Technical Activities Board and chair of the emerging technologies initiatives and is a proud Honorary Kentucky Colonel.

Summary:

This presentation will discuss challenges and opportunities created through increased data acquisition and data retention. Various sources of data and stages of data and information flow will be highlighted and addressed. The rationale for addressing Big Data as a special case requiring attention will be presented.  Discussion of issues related to a) Computation for Big Data using various tools, algorithms, and architectures, b) Data Storage using cloud architecture and distributed systems, c) Data Retrieval from structured, unstructured and multimedia sources, d) Application approaches to access Big Data through mobile and other devices, e) Analytic and Data Mining techniques for big data. All these issues are wrapped with a need for increase Security and Privacy to guarantee acceptability in various areas such as financial, health and education.





                           Keynote Speaker 5:  Designing Machine Learning Systems that Scale

                                                                   Dr. Nicklaos Vasiloglou
                                                              Innovator, Comrise Technology

Biography:

Nikolaos Vasiloglou holds a Ph.D. from the Department of Electrical and Computer Engineering at Georgia Institute of Technology.  His thesis is focused on scalable machine learning over massive datasets, including dimensionality reduction within manifold methods of isometry and convexity.
After graduating from Georgia Tech, he founded the companies Analytics1305 and Ismion. He then architected and developed the PaperBoat machine learning library, which has been successfully integrated and used in the LogicBlox and HPCC Systems platforms. Nikolaos has applied his skills and knowledge as a machine learning consultant to Predictix, Revolution Analytics, Damballa, Comrise Technology and LexisNexis.
Additional accomplishments include a pending patent on choice set modeling for retail forecasting problems, and developing applications of KD-trees in statistical analysis(2-point correlation),  and kernel density estimation. His work with multidimensional indexing structures, including caching and parallelization, is focused on large-scale kernel algorithms such as Kernel PCA Support Vector Machines and Neural Networks.

Summary:

There has been a growing effort in building machine learning platforms/libraries that scale in the real world. Different teams have tried to solve that problem but they have only succeeded in small areas in machine learning. The main problem is that usually database experts use systems developed for data management and they try to stretch machine learning algorithms to fit in their platform. Machine learning scientists do the opposite. They are trying to stretch data volumes to fit into their algorithm requirements. In this talk we will give a brief overview of the factors that a machine learning architect will have to consider in order to build a successful machine learning infrastructure. We will show why HPCC satisfies most of the requirements and what additional changes the development team is willing to do in order to bring it closer to solving the problem.

 

 

 

                Keynote Speaker 6:  Big Data: a big breakthrough, a major step backward, or a déjà vu

                                                                                                       Dr. Chung-Min Chen
                                       Chief Scientist, ACS (a Telcordia Technologies subsidiary)
                                                                     Telcordia Technologies, USA

Biography:

During his career, Chung-Min has been passionate about finding efficient ways to process and make sense of large scale data.  He has spent most of his professional time on developing innovative algorithms and building scalable databases and analytics systems to support telecom network operation and other applications.  His research interest spans across areas in database systems, stream processing, machine learning, parallel & distributed computing, mobile data, and mobile ad hoc network.   Currently, he is interested in researching, developing, and applying big data and analytics technologies to problems in cyber security, telecom OSS, and telematics.

Chung-Min has published over 50 research papers in journals and conferences including The Journal of the ACM, IEEE Trans. on Knowledge and Data Engineering, ACM

Transactions on Sensor Networks, IEEE Trans. on Mobile Computing, IEEE/ACM Trans. on Networking, IEEE J. SAC, INFOCOM, ACM SIGMOD, KDD, EDBT, ICDE, and ICDCS. Hereceived the Newcomer Paper Award of ACM PODS 2002.

Chung-Min joined Applied Research of Bellcore/Telcordia in 1998. During 2006-2011, he headed Telcordia’s applied research center in Taiwan, overseeing its activities in R&D, professional consulting, and customer engagement. Chung-Min was an Adjunct Professor at National Taiwan University (2008-2011) and an invited speaker at the 2001 Data Mining Summer School at Rutgers University. He also served as the Chair of US ANSI expert group to Working Group 17 (Mobile Devices for ITS Applications) of ISO TC-204 (Intelligent Transportation System). He received PhD in Computer Science from University of Maryland at College Park and B.S. in Computer Science from National Taiwan University.


Summary:

Many people believe the recent offerings from the big data camp (Hadoop, NoSQL and the like) represent a big breakthrough in handling very large scale data. Some don’t, and call it a major step backward. And, doesn’t it sound a bit déjà vu for us who have witnessed the research and technological development in distributed OS, parallel database, and parallel and distributed computing over the past two decades? In this talk, I will reflect on the above view points and share my thoughts on what really stands out from the big data technologies and how they can help to improve our business operations?

Disclaimer: The view expressed and materials presented in this talk represent the speaker’s own personal views on the subject and do not necessarily represent the views of his employer.
 

 

              Keynote Speaker 7:  Enabling Cloud Computing from Hype to Reality
                                                                                                       Xuewen (Sean) Gong ,
                                           Director of Huawei Reliability Technology Committee,
                                                                     Huawei Technologies, China

Biography:

Xuewen (Sean) Gong has been working for Huawei more than 15 years, he is working as director of Huawei reliability technology committee, leading research and development on RAS (Reliability, Availability, Serviceability), especially on Fault tolerant, Failure Prediction and Self Healing for emerging ICT technologies and solutions, before this position he was the head of architecture and DFX in Huawei USA R&D center. He received M.Sc degree from Huazhong University of Science and Technology before joining Huawei.








Summary:

Cloud computing has been developing fast in the past few years, more and more enterprises have deployed or planning to deploy it, but sometime the cloud computing is not so beautiful in reality world, e.g. a lot of outages happened, such the well-known Amazon cloud outages, which raised doubt on cloud computing. In this presentation, some concerns on cloud computing deployment will be discussed from engineering perspective, and some Huawei’s practice will be also introduced.