UCL Engineering


Spring into STEM | Applying Statistics to Improve Online Recommendations | Virtual Lecture Series

16 May 2022, 12:00 pm–1:00 pm

Abstract shapes

As a part of the Spring into STEM Lecture Series, UCL School of Management’s Yiting Deng will be hosting a session on; Applying Statistics to Improve Online Recommendations. In the talk, Yiting discusses the challenges in recommendation systems and why only a few (if any) address and accommodate these challenges.

This event is free.

Event Information

Open to

All | UCL staff | UCL students | UCL alumni






Grace Gaywood – UCL School of Management


United Kingdom

Recommendation systems for contexts such as online news or online retailing are prevalent in our daily life. There are several challenges in such recommendation systems:

  1.  how to make initial recommendations to users with little or no response history,
  2. how to learn user preferences for items, and
  3. how to scale the recommendation system across many users and items, with many potential demographics and attributes respectively.

Through Yiting Deng’s research she designed a statistical method that can efficiently handle these issues simultaneously. Her online experiments in an online retail setting demonstrate the advantage of this method in comparison to existing methods.

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About the Speaker

Yiting Deng

Assistant Professor of Marketing and Analytics at UCL School of Management

Yiting Deng is an Assistant Professor of Marketing and Analytics at the UCL School of Management. Her main research interests are in digital platforms, advertising, media consumption, and two-sided markets.

More about Yiting Deng

Other events in this series