Fwd: [Hyd-ACM] Cloud BigData Internals- a researcher's perspective. 17th Aug 2012
Aditya Rao
From: Ramesh Loganathan <ram...@progress.com>
Date: Thu, Aug 2, 2012 at 4:12 PM
Subject: [Hyd-ACM] Cloud BigData Internals- a researcher's perspective. 17th Aug 2012
To: "hydera...@googlegroups.com" <hydera...@googlegroups.com>, HydStartups <hydst...@googlegroups.com>
Workshop on Cloud BigData Internals- a researcher's perspective
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The Hyderabad ACM Chapter and ITsAP Hyderabad take great pleasure in inviting you to a seminar Cloud Deep-Dive. This seminar includes deeper discussion on real cloud use-cases from adoption in enterprises followed by deep-dive talks on some real Cloud use-cases. Include talks on some aspects of cloud internals in the context of BigData, data federation, information retrieval and other analytics approaches followed by a panel discussion
Date: 17th August 2012. Friday. Venue: Progress Software, Hyderabad Registration: Click here to register
Program:
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MapReduce, Pregel and the Art of Thinking Parallel
by Dr.Shailesh Kumar
Data is generated today at a tremendous rate in many domains - sciences, retail, web, medicine, social, remote sensing, etc. This data contains wealth of insights about the nature of the process that generated it, the cause and effect relationships among variables, latent structures and hidden trends in it, etc. A number of distributed and massively parallel computing paradigms have been developed in the last few decades to deal with the ever growing demand for large scale number crunching to discover insights, build predictive models, and drive real time decisions from this ever growing data.
In this talk we will introduce two such distributed computing paradigms, MapReduce (Hadoop is based on MapReduce) and Pregel, the two most common and complimentary number crunching platforms in cloud computing. Through a number of "beautiful", practical and large scale parallel algorithms we will explore the underlying philosophy, the simplicity of use, and the nuances and limitations of these paradigms. In the process, we will also develop some insight into the "art of thinking parallel".
About Dr. Shailesh Kumar
Dr. Shailesh Kumar is a Member of Technical Staff at Google, Hyderabad. Prior to joining Google, he has worked as a Principal Dev. Manager at Microsoft (Bing) Hyderabad, Sr. Scientist at Yahoo! Labs Bangalore, and Principal Scientist at Fair Isaac Research in San Diego, California. Dr. Kumar has over fifteen years of experience in applying and innovating machine learning, statistical pattern recognition, and data mining algorithms to hard prediction problems in a wide variety of domains including information retrieval, web analytics, text mining, computer vision, retail data mining, risk and fraud analytics, and bioinformatics. He has publishedover 20 conference papers, journal papers, and book chapters and holds over a dozen patents in these areas. He has also served on the program committees and review committees of several international conferences and journals. Dr. Kumar received his PhD in Electrical and Computer Engineering in Dec. 2000 (with a specialization in statistical pattern recognition and data mining) and Masters in Computer Science in May 1997 (with a specialization in artificial intelligence and machine learning), both from the University of Texas at Austin, USA. He received his B.Tech. in Computer Science and Engineering from the Institute of Technology, Banaras Hindu University in 1995.
Automatic Construction of Big Semantic Data on Cloud
by Dr. Vasudeva Varma
Enabling scalable semantic search is a key challenge as it involves identification of named and non-named entities, relations that connect entities as well as naming these relations. State of the art systems employfact gathering or knowledge harvesting techniques using patterns and a set of seed "facts" to discover new candidate facts to improve recall. Reasoning-enhanced systems check the quality of the candidate facts to improve precision. In this talk, I will focus on (a) knowledge extraction and Knowledge Base population (KBP) tasks by extracting the information about the entities with reference to external knowledge sources (such as world wide web). The goal is automatically create Wikipedia Info-box like structures for a given text document about an entity and large number of unstructured but related document collection (b) enabling semantic search using building blocks of entity, relation and relevant metadata extraction to create an ontology andinfer the semantics of the given text. Cloud is a critical infrastructure to achieve this challenging task.
About Dr. Vasudeva Varma
Vasudeva Varma is a professor at International Institute of Information Technology, Hyderabad. His research interests include search (information retrieval), information extraction, information access, knowledge management, cloud computing and software engineering. He is heading Search and Information Extraction Lab and Software Engineering Research Lab at IIIT Hyderabad. He is also the chair of Post Graduate Programs since 2009.He published a book on Software Architecture (Pearson Education) and over hundred technical papers in journals and conferences. In 2004, he obtained young scientist award and grant from Department of Science and Technology, Government of India, for his proposal on personalized search engines. In 2007, he was given Research Faculty Award by AOL Labs.
He co-founded SETU Software Systems Pvt Ltd, a technology start-up along with Dr. Prasad Pingali (Vasu’s first PhD student) which is focused on solving information access problems using unstructured data analytics. He was visiting professor at UPV, Valencia, Spain (Summer 2007), UBO, Bretagne, France (Summer 2009) and Language Technologies Institute, CMU, Pittsburgh, USA (Summer 2010)
He obtained his Ph.D. from the Department of Computer and Information Sciences, University of Hyderabad in 1996. Prior to joining IIIT Hyderabad, he was the president of MediaCognition India Pvt. Ltd and Chief Architect at MediaCognition Inc. (Cupertino, CA). Earlier he was the director of Engineering and research at InfoDream Corporation, Santa Clara, CA. He also worked for Citicorp and Muze Inc. in New York as senior consultant.
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Aditya R Rao
Vice Chair, Membership Development Committee (MDC), IEEE CS
Cell: +91 988 510 4058 / Off + 91 40 660 52666
http://adityarrao.tumblr.com
http://www.computer.org/portal/web/chapters/board