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| Invited Speakers |
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Jeffrey Voas, Ph.D
Computer Scientist,
National Institute of Standards and Technology
Computer Security Division
Maryland, USA
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About Dr. Jeffrey Voas
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Jeffrey Voas is a computer scientist at the US National Institute of Standards and Technology (NIST) in Gaithersburg, Maryland. Before joining NIST, Voas was an entrepreneur and co-founded Cigital in 1992. After 13 years at Cigital, Voas accepted a director position at Science Applications International Corporation (SAIC) and was named an SAIC Technical Fellow from 2005 to 2009. He has served as the IEEE Reliability Society President in 2003-2005 and 2009-2010, and serves as the IEEE Computer Society¡¯s Second Vice President in 2010. Voas is the Director-elect of the IEEE Division VI* in 2010, and starting the two-year term of the directorship in 2011.
Voas
co-authored two John Wiley books: Software Assessment: Reliability, Safety, and Testability in 1995 and Software Fault Injection: Inoculating Software Against Errors in 1998, is currently an Associate Editor-In-Chief of IEEE¡¯s IT Professional magazine, and is on the editorial board of IEEE Computer Magazine. He was one of two people named IEEE Reliability Engineer of the Year in 2000. He received two U.S. patents and has over 170 publications. Voas received his undergraduate degree in computer engineering from Tulane University in 1985), and received his M.S. and Ph.D. in computer science from the College of William and Mary in 1986 and 1990, respectively. Voas performed a two-year post-doc for the National Research Council from 1990 to1992. He is a Fellow of the IEEE.
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The Grand Challenges of Cloud Computing
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Cloud computing is the most recent phenomenon to emerge within the IT sector; however, it carries its own mystique. Many academics consider it nothing more than an updated version to the principles of distributed computing. Many businesses view it as a Godsend allowing them simply a quick and inexpensive approach to increased storage and computing power without the expense of building it in-house. Others view it simply a model for the distribution of computing and storage capabilities that will be delivered in a manner similar to how you currently receive electricity and water into your home. That is, you do not know where it comes from just as long as it arrives. However, others fear it as a centralized way to take control due to features, such as data ¡°lock-in¡±, whereby your data can be taken hostage by a particular cloud provider, therefore negating any proposed economic upside. Those in this camp also fear the security and privacy ramifications of centralization, and argue that in the long run, it will cost more when your data becomes stolen, breached, or lost.
In this talk, we will explore these issues as well as what are the grand challenge problems facing the cloud computing paradigm. We will also explore what it means to take the human further out of the IT infrastructure loop, a side-effect of this form of delivering computing services. In summary, this talk will cut through the mainstream media hype, and give a realistic assessment of the key cloud computing concerns and myths.
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Jaideep Srivastava, Ph.D
Computer Science and Engineering
University of Minnesota
Minneapolis, Minnesota, USA
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About Professor Jaideep Srivastava
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Jaideep Srivastava has a Bachelor degree from the Indian Institute of Technology, Kanpur, India and MS and PhD degrees from the University of California, Berkeley. He is a Professor of Computer Science & Engineering at the University of Minnesota. He has established and led a laboratory that conducts research in databases, multimedia systems, and data mining. Dr. Srivastava has an active collaboration with the technology industry, both for research and technology transfer, and is an often-invited participant in technical and technology strategy forums. He has authored or co-authored over 225 papers and book chapters. A series of prototype software systems have built in his laboratory to evaluate and validate our research results; and have acted as vehicles of technology transfer.
Dr. Srivastava has significant experience in the industry, in both consulting and executive roles. Specifically he has led a corporate data mining team at Amazon and spent two years as the Chief Technology Officer for Persistent Systems. In addition, he oversaw the redesign of the training and technical vitalization program for 2,200+ engineers; and also established collaborative research programs with a number of academic institutions. He has served as technology advisor to industry and governments.
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Social Games and Virtual Worlds as Macroscopes of Human Behavior
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Observation and analysis of a phenomenon at unprecedented levels of granularity not only furthers our understanding of it, but also transforms the way it is studied. For instance, invention of gene-sequencing and computational analysis transformed the life sciences, creating fields of inquiry such as genomics, proteomics, etc.; and the Hubble space telescope has furthered the ability of humanity to look much farther beyond what we could otherwise.
With the mass adoption of the Internet in our daily lives, and the ability to capture high resolution data on its use, we are at the threshold of a fundamental shift not only in our understanding of the social and behavioral sciences, but also the ways in which we study them. Massively Multiplayer Online Games (MMOGs) and Virtual Worlds (VWs) have become increasingly popular and have communities comprising tens of millions. They serve as unprecedented tools to theorize and empirically model the social and behavioral dynamics of individuals, groups, and networks within large communities. This talk introduces the Virtual World Exploratorium, a multi-institutional, multi-disciplinary project which uses data from commercial MMOGs and VWs to study many fields of social science, including sociology, social psychology, organization theory, group dynamics, macro-economics, etc. We will summarize finding from many of these disciplines.
Given the amount of data being generated (e.g. all of Zynga's games on Facebook generate around 3 terabytes of data a day), there are exciting new challenges for the computer science community, especially in the areas of data management, data mining, and algorithms. We also present some findings in these areas.
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