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Dr Vivekanand Gopalkrishnan

Research Director

Vivekanand Gopalkrishnan is the director of research for the Deloitte Analytics Institute. He has nearly 20 years of experience in research, teaching, consulting on the development of practical solutions to real-world issues using analytics.

Vivek has advised clients on strategies for driving data-driven insights, and specialises in architecting innovative solutions that mine insights even when the data is not “well-behaved.” His research covers data mining, machine learning and data warehousing, and he has published over 50 papers in these fields.

Vivek continues to actively serve the academic and research communities. He is on the editorial boards and review committees of leading research journals, and on the program committees of top international data mining and information management conferences. As a passionate educator, he continues to guide university academic programmes and research councils in analytics.

Industries

  • Public Sector
  • Financial Services
  • Telecommunications
  • Pharmaceuticals
  • Media

Career highlight

Vivek loves to change perceptions and shape best practices in industry and in research. One of his favourite projects helped a leading media client re-evaluate their data strategy by embedding advanced analytics and saved huge expenses in infrastructure development.

Latest publications

In accordance with the ACM copyright policies, I make private copies of my papers available for personal use on this page.

Big Data, Big Business: Bridging the Gap1

Big Data Mining, BigMine  | Aug 2012 | Beijing, China

Big Data, Big Business: Bridging the Gap (BigMine 2012). © ACM, [2012]. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in BigMine 2012, see http://dl.acm.org/citation.cfm?id=2351318.

[1] Full citation:
Big Data, Big Business: Bridging the Gap

Vivekanand Gopalkrishnan, David Steier, Harvey Lewis, James Guszcza
ACM BigMine Workshop on
Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, pp. 7-11, 2012

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