The quality of the search experience on an e-commerce site plays a critical role in customer conversion and the growth of the e-commerce business.

In this talk, Dr Haixun Wang will discuss the current status and challenges of product search. In particular, highlighting the significant amount of effort it takes to create a high-quality product search engine using classical information retrieval methods.

Dr Wang will discuss how recent advances in NLP and deep learning, especially the advent of large pre-trained language models, may change the status quo. While embedding-based retrieval has the potential to improve classical information retrieval methods, creating a machine learning-based, end-to-end system for general-purpose, web search is still extremely difficult.

Neverthless, Dr Wang will argue that product search for e-commerce may prove to be an area where deep learning can create the first disruption to classical information retrieval systems.

This session will be conducted online via Zoom:


Professor Helen Huang


Dr Haixun Wang

Currently an IEEE fellow, editor in chief of IEEE Data Engineering Bulletin, and a VP of Engineering and Distinguished Scientist at Instacart. Before Instacart, Dr Wang was a VP of Engineering and Distinguished Scientist at WeWork, a Director of Natural Language Processing at Amazon, and he led the NLP team working on Query and Document Understanding at Facebook. 

  • 2013 to 2015, worked with Google Research on natural language processing.
  • 2009 to 2019, led research in semantic search, graph data processing systems, and distributed query processing at Microsoft Research Asia.
  • 2009, researcher at IBM T.J Watson Research Center.

In 2000, Dr Wang received his PhD degree in Computer Science from the University of California, Los Angeles. He has published more than 150 research papers in referred international journals and conference proceedings. He served as PC Chairs of conferences such as SIGKDD'21, and he is on the editorial board of journals such as IEEE Transactions of Knowledge and Data Engineering (TKDE) and Journal of Computer Science and Technology (JCST).

  • Winner of best paper award in ICDE 2015.
  • Winner of 10-year best paper award in ICDE 2010.
  • Winner of best paper of ER 2009.


About Data Science Seminar

This seminar series will be run as weekly sessions and is hosted by ITEE Data Science.



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