Talks & Seminars
Unlocking Information in Data
Dr. Nandit Soparkar, Ubiquiti Inc., USA
Date & Time: November 22, 2007 11:00
Venue: Conference Room, 01st floor, 'C' Block, Kanwal Rekhi Building
This presentation, replete with technology demonstrations, will discuss some cutting-edge techniques to leverage existing information in large datasets. Much of our software is commercial, and some recent approaches are supported by multi-year grants by the US government (eg, National Science Foundation). This presentation will discuss and demonstrate some of our key technologies. Our software is used for root-cause analysis, online rapid diagnostics, and early-warning systems in diverse areas such as the transportation sector (ie, automotive, fleet, aviation), and in healthcare (payers, providers, pharma). Ubiquiti provides solutions for information analysis, with special emphasis on text data and large datasets. Instead of the tedious manual analysis required to discover and exploit the information often hidden in the data, Ubiquiti technologies quickly extract the key information. Our technologies can identify useful, domain-specific, detailed information contained in data from essentially all sources including unstructured text. All information, the structured as well as the unstructured, are combined by our technologies to help identify important events, opportunities and trends. Such derived information is combined with in-house knowledge in decision-making. We have provided our solutions to the commercial for several years.
Speaker Profile:
Dr. Nandit Soparkar is involved with business & technical development at Ubiquiti Inc., a high-tech company that provides data analysis software. He has been a visiting faculty member, and a former tenure-track professor, in the College of Engineering at Univ. Michigan, Ann Arbor. He has been an advisor to software companies (e.g., B-Bop, Aalayance, OTelNet) to provide technical advice. In research, he examined time-constrained transaction management, data mining & analyses technology, and logic-enhanced memory for data-intensive computing. He received an IBM Fellowship, and a National Science Foundation Career Award (formerly, Presidential Young Investigator Award); he worked at AT&T Bell Labs at Murray Hill, and the IBM TJ Watson Research Center in New York. He has published and pending books, research papers, patents; and has performed peer reviews for research and business development. He has a B.Tech (Comp.Sci. & Engin.) from IIT Delhi; and M.S. and Ph.D. degrees (Comp.Sci.) from Univ. Texas at Austin, and is in the Exec. MBA program at Univ. Michigan, Ann Arbor.
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