Overstock.com and RichRelevance Appoint Peer Review Committee for RecLab Prize

Leaders from academia and industry will review RecLab Prize submissions and select up to ten teams to move on to compete for $1 million cash award

San Francisco, CA – Jan. 11, 2012 –– As Overstock.com and RichRelevance continue to accept entries for the RecLab Prize on Overstock.com, the companies today announced the formation of the Prize’s Peer Review Committee.  Leading researchers Eugene Agichtein of Emory University, Oliver Downs of Analytical Insights, Inc., and Alexander Tuzhilin of New York University Stern School of Business will join RichRelevance Chief Scientist Darren Vengroff to review all Prize submissions and select the ten semifinalists who will advance to compete for a cash award of up to $1 million.

The RecLab Prize on Overstock.com, which encourages innovation in retail personalization, will continue to receive submissions at overstockprize.com until March 1, 2012.  Current teams represent leading academic institutions around the world, including BYU, Hong Kong University and Warsaw University of Technology, among others.

“Algorithm development is one of the most complex tasks in technology today, and we’ve assembled some of the brightest minds in computer and mathematical science to help us oversee the RecLab Prize on Overstock.com,” said Darren Vengroff, Chief Scientist of RichRelevance. “As we move further along into the competition, the committee will ensure that the best teams or individuals get the recognition they deserve. We’re excited to welcome such notable visionaries into the RecLab Prize and look forward to garnering their expertise.”

The Peer Review Committee for the RecLab Prize on Overstock.com

The Peer Review committee brings deep expertise in mathematics and computer sciences and years of experience at the top of their fields.  The committee will review submissions based on novelty of design and expected effectiveness at generating sales lift. It will also ensure that the semifinalists represent a unique, diverse set of approaches to the problem, rather than a large number of subtle variants of a single approach. Members include:

  • Eugene Agichtein is an Assistant Professor in the Math and Computer Science department at Emory University, and is on the core faculty of the Biomedical Informatics program. Eugene founded and leads the Emory Intelligent Information Access Laboratory (IR Lab). He is a recipient of the “Best Student Paper” award at the ICDE 2003 conference, and of the “Best Paper” awards at the SIGMOD 2006 and SIGIR 2011 conferences. Eugene received a PhD in Computer Science from Columbia University, and a BS in Engineering from The Cooper Union.
  • Oliver Downs is President and Chief Scientist at Analytical Insights, Inc. His extensive background in algorithm design has resulted in 21 U.S. patents pending in the fields of Bayesian prediction, statistical estimation, outlier detection, real-time GPS data processing, and 10 granted patents in the fields of Quantum Optimization Algorithms, Dynamic Time Series Prediction, Location-based Data Probes, Anomaly Detection and Scalable Spatial Search. Previously, Oliver was Chief Scientist at Atigeo where he developed a learning semantic platform for personalization and search. He holds PhD and MA degrees in Applied and Computational Mathematics from Princeton University and BA, MA and MSc degrees in Experimental & Theoretical Physics, from the University of Cambridge, UK.
  • Alexander Tuzhilin is a Professor of Information Systems and an NEC Faculty Fellow at the NYU Stern School of Business. His current research interests include data mining, personalization, recommender systems and CRM. He has served on the Editorial Boards of several leading journals in his areas of expertise, and currently serves on the boards of the ACM Transactions on Management Information Systems, the INFORMS Journal on Computing (as an Area Editor) and the Data Mining and Knowledge Discovery Journal. His various academic and industrial activities have been featured in major media publications, including The New York Times, The Wall Street Journal, Business Week and the Financial Times. Alexander received his BS in Mathematics from NYU, his MS in Engineering Economics from Stanford University and his PhD in Computer Science from the Courant Institute of Mathematical Sciences at NYU.
  • Darren Vengroff is responsible for all of RichRelevance’s analytical and machine learning development—from high-level strategy and analytics, to strategic implementation plans. From startups to industry leaders Amazon.com and Goldman Sachs, Darren has designed and built a variety of world-class, customer-focused, scalable applications. Prior to RichRelevance, Darren was CTO and co-founder of Pelago, Inc. (makers of Whhrl) where he oversaw Pelago’s technology and actively supported product definition, fundraising, and business development. Before Pelago, Darren was a Principal Engineer at Amazon.com and a Vice President at Goldman Sachs. Darren holds an MSc and PhD in Computer Science from Brown University, where he studied I/O-efficient algorithms with Jeff Vitter, and a B.S.E. in Computer Science with Highest Honors from Princeton University.

“The RecLab approach to personalization innovation cleverly addresses the way we commonly need to treat proprietary data industry-wide today and provides a great framework to catalyze this industry through an exciting and practical competition,” said Peer Review Committee Member, Oliver Downs. “I am extremely honored to have been selected as part of this committee and look forward to working with the teams and individual contestants, RichRelevance and Overstock.com in bringing this innovation to the market.”

About the RecLab Prize on Overstock.com

  • In May of 2011, RichRelevance and Overstock.com unveiled the RecLab Prize on Overstock.com, a contest that provides a cash reward of up to $1 million to the researcher or research team who can achieve a measurable lift over existing product recommendations on Overstock.com.
  • RecLab Prize contestants are granted access to a high-quality and comprehensive synthetic dataset via RichRelevance’s open-source RecLab project, which enables researchers to develop their algorithms against synthetic data and then test against real data.
  • Top performing algorithms will be exposed to real data and will run live within the RichRelevance cloud environment (as real product recommendations to Overstock.com’s customers).
  • The RecLab Prize rewards the highest performing individual or team based on the results delivered within a defined judging period (up to $1 million for a 10% or greater lift).
  • · To ensure that all eligible teams are able to participate, RichRelevance and Overstock.com have extended the contest deadline to March 1, 2012. The contest is still actively accepting registrants and teams and individuals interested in participating should visit: overstockprize.com to register.

Additional Resources

About Overstock.com
Overstock.com, Inc. is a Savings Engine offering brand-name merchandise at discount prices. The company offers its customers an opportunity to shop for bargains conveniently, while offering its suppliers an alternative inventory distribution channel. Overstock.com, headquartered in Salt Lake City, is a publicly traded company listed on the NASDAQ Global Market System and can be found online at http://www.overstock.com and http://www.o.co. Overstock.com regularly posts information about the company and other related matters on its website under the heading “Investor Relations.” Overstock.com® is a registered trademark and Savings Engine™ are trademarks of Overstock.com, Inc. All other trademarks are the property of their respective owners.

AboutRichRelevance
RichRelevance powers personalized shopping experiences for the world’s largest and most innovative retail brands, including Walmart, Sears, Target and others. Founded and led by the e-commerce expert who helped pioneer personalization at Amazon.com, RichRelevance helps retailers increase sales and customer engagement by recommending the most relevant products to consumers regardless of the channel they are shopping. RichRelevance has delivered more than $3 billion in attributable sales for its retail clients to date, and is accelerating these results with the introduction of a new form of digital advertising called shopping media which allows manufacturers to engage shoppers where it matters most – in the digital aisles on the largest retail sites in world. RichRelevance is headquartered in San Francisco, with offices in New York, Seattle, Boston and London. For more information, please visit www.richrelevance.com

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ABOUT RichRelevance
RichRelevance is the global leader in experience personalization, driving digital growth and brand loyalty for more than 200 of the world’s largest B2C and B2B brands and retailers. The company leverages advanced AI technologies to bridge the experience gap between marketing and commerce to help digital marketing leaders stage memorable experiences that speak to individuals – at scale, in real time, and across the customer lifecycle. Headquartered in San Francisco, RichRelevance serves clients in 42 countries from 9 offices around the globe.
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