Anand Rajaraman

Anand RajaramanAnand Rajaraman is a serial entrepreneur, venture capitalist, and academic based in Silicon Valley. He is a Founding Partner at Rocketship VC, an innovative venture capital firm that uses data mining and machine learning to find promising startup invstments all over the world. Rajaraman's investments include Facebook (one of the earliest angel investors in 2005), Lyft, Aster Data Systems (acquired by Teradata), Efficient Frontier (acquired by Adobe), Neoteris (acquired by Juniper), Transformic (acquired by Google), and several others. Rajaraman was, until recently, Senior Vice President at Walmart Global eCommerce and co-head of @WalmartLabs, where he worked at the intersection of social, mobile, and commerce. He came to Walmart when Walmart acquired Kosmix, the startup he co-founded, in 2011. Kosmix pioneered semantic search technology and semantic analysis of social media. In 1996, Rajaraman co-founded Junglee, an e-commerce pioneer. As Chief Technology Officer, he played a key role in developing Junglee's award-winning Virtual Database technology. In 1998, Amazon.com acquired Junglee, and Rajaraman helped launch the transformation of Amazon.com from a retailer into a retail platform, enabling third-party retailers to sell on Amazon.com's website. He is also a co-inventor of Amazon Mechanical Turk, which pioneered the concepts of crowdsourcing and hybrid Human-Machine computation. As an academic, his research has focused at the intersection of database systems, the Web, and social media. His research publications have won several awards at prestigious academic conferences, including two retrospective 10-year Best Paper awards at ACM SIGMOD and VLDB. In 2012, Fast Company magazine named Rajaraman in its list of '100 Most Creative People in Business'. In 2013, he was named a Distinguished Alumnus by his alma mater, IIT Madras. In addition to acting as a consulting assistant professor in the Computer Science Department at Stanford University, California, he is a spe Read More Read Less

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Mining of Massive Datasets8 % NR
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Mining of Massive Datasets2 % NR
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05 Jun 2012
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