Visiting Speaker
Julian McAuley
Assistant Professor, UCSD
Combining Generative Models with User Interactions for Product Recommendation and Design
Thursday
Mar 14, 2019
Watch video
11:00 am
177 Huntington Ave
11th floor

Predictive models of human behavior--and in particular recommender systems--learn from large graphs of historical interactions among users and items, in order to make personalized predictions that adapt to the needs, nuances, and preferences of individuals. After introducing the current state-of-the-art in personalized recommendation technology, in this talk I'll cover two emerging directions in recommender systems research: (1) Work that incorporates Recommender Systems with NLP techniques, such as developing personalized language models; and (2) Work that incorporates generative modeling techniques into recommender systems, including using recommender systems to facilitate the design of new products.

About the speaker
Julian McAuley has been an Assistant Professor in the Computer Science Department at the University of California, San Diego since 2014. Previously he was a postdoctoral scholar at Stanford University after receiving his PhD from the Australian National University in 2011. His research is concerned with developing predictive models of human behavior that leverage large volumes of user interactions and social network data.. Website: https://cseweb.ucsd.edu/~jmcauley/
Visiting Speaker
Julian McAuley
Assistant Professor, UCSD
Combining Generative Models with User Interactions for Product Recommendation and Design
Thu
Mar 14, 2019
11:00 am
177 Huntington Ave
11th floor
ADD to calendar

Predictive models of human behavior--and in particular recommender systems--learn from large graphs of historical interactions among users and items, in order to make personalized predictions that adapt to the needs, nuances, and preferences of individuals. After introducing the current state-of-the-art in personalized recommendation technology, in this talk I'll cover two emerging directions in recommender systems research: (1) Work that incorporates Recommender Systems with NLP techniques, such as developing personalized language models; and (2) Work that incorporates generative modeling techniques into recommender systems, including using recommender systems to facilitate the design of new products.

about the speaker
Julian McAuley has been an Assistant Professor in the Computer Science Department at the University of California, San Diego since 2014. Previously he was a postdoctoral scholar at Stanford University after receiving his PhD from the Australian National University in 2011. His research is concerned with developing predictive models of human behavior that leverage large volumes of user interactions and social network data.. Website: https://cseweb.ucsd.edu/~jmcauley/