Using Data Science to Increase Shopper Productivity

Share

Seats: 200

Sponsored by the IEEE Computer Society San Diego Chapter

Co-Sponsored by IEEE Communications Society, IEEE Consumer Electronics Society and IEEE Youmg Professional of San Diego

 


Parking will be reimbursed for $5

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.



  Date and Time

  Location

  Contact

  Registration


  • Atkinson Hall, 9500 Gilman Drive #0436
  • La Jolla, California
  • United States 92023
  • Click here for Map
  • Natasha Balac, Ph.D., IEEE Computer Society San Diego Chapter Chair

    Charlie Bird, IEEE Computer Society San Diego Chapter Vice Chair 

     

  • Registration closed


  Speakers

Geoffrey Hueter, Ph.D. of Certona Corporeation

Topic:

Using Data Science to Increase Shopper Productivity

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.

 

Biography:

Geoff 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.

Email:

Address:10431 Wateridge Circle, Suite 200, San Diego, California, United States, 92121





Agenda

Networking and Refreshments 6:30-7, talk 7-8, Q&A 8-8:15.

Park and pay at a Visitor spot in Hopkins Parking Structure: http://seminarseries.ucs d.edu/getting-here/

Parking App and information: https://transportation.ucsd.edu/parking/visitor/index.html

If coming by Lyft, Uber or Cab then navigate to Atkinson Hall.



Cost:  Free for IEEE and UCSD; $5 cash only for all others to cover refreshments.

Location: Atkinson Hall, 9500 Gilman Drive #0436, La Jolla, CA 92093.

Questions:  IEEE San Diegowww.sdieee.org.