Using Data Science to Increase Shopper Productivity πŸ—“

Meeting
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Sponsored by the IEEE Computer Society San Diego Chapter
Co-Sponsored by IEEE Communications Society, IEEE Consumer Electronics Society and IEEE Young Professional of San Diego

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Meeting Date: December 6, 2018
Time: 6:30 PM Networking & Food; 7:00 PM Presentation
Speaker: Geoffrey Hueter, Ph.D. of Certona Corporation
Location: San Diego
Cost: none
RSVP: requested, through website
Event Details: IEEE vTools

Summary: Recommender systems pose unique challenges to data scientists because the effectiveness of the recommendations can only be assessed by the response of the consumer. In this regard recommenders can be thought of as feedback control systems, whereby the control model parameters are adjusted to optimize the desired outcomes of the business.

The presentation will focus on various aspects of setting up a recommender system, including representation and collection of behavioral signals, development and testing of machine learning algorithms, and architecting a platform for combining past information with live inputs to make real-time decisions about what to next show the consumer. The presentation will also describe the experience of Certona Corporation in creating a commercial personalization platform that blends data science with business rules to satisfy the practical requirements of merchandizers and other non-scientist users.

Bio: Geoffrey Hueter is the CTO and Co-Founder of Certona Corporation, the leader in real time, AI powered omnichannel personalization for the world’s largest B2C and B2B brands and retailers. Dr. Hueter leads the invention of Certona’s innovative proprietary technologies, which have been awarded 8 patents to date. Dr. Hueter holds a Ph.D. in Physics from the University of California at San Diego, where he studied gamma ray bursts and was part of the team that developed the Gamma Ray Observatory. After receiving his Ph.D., Dr. Hueter studied neural networks with industry pioneers Robert Hecht Nielsen and Bart Kosko and then joined HNC Software (subsequently acquired by Fair Isaac), a startup that led the early commercialization of neural network (aka deep learning) technology.

As a Staff Scientist and Director, Dr. Hueter managed the development of intelligent machine vision systems, self-optimizing control systems, and other innovative applications of neural networks and cognitive systems, including several Department of Defense Small Business Innovation Research (SBIR) programs. Dr. Hueter is the author of over a dozen papers on astrophysics, neural networks, and numerical modeling and holds the rare distinction of both hitting a home run and scoring on the Putnam test.