Biography

Bing Liu is a Distinguished Professor and Peter L. and Deborah K. Wexler Professor of Computing at the University of Illinois at Chicago (UIC). He received his PhD in Artificial Intelligence from the University of Edinburgh. Before joining UIC, he was a faculty member (associate professor) at School of Computing, National University of Singapore (NUS). He was also with Peking University for one year (2019-2020).

• Current Research Interests: Lifelong or continual learning, open-world AI and continual learning, continual learning language models and dialogue systems, natural language processing, Machine learning, Artificial General Intellgience (AGI).
• Previous research interests include sentiment anaysis and opinion mining, fake opinion detection, PU learning, data mining and Web mining.


• Research Publications: He has published extensively in top conferences and journals such as NeurIPS, ICML, ICLR, ACL, EMNLP, KDD, WWW, AAAI, IJCAI, TKDE, TWEB, CL, etc. His papers with citations can be found from his Google Scholar page (or his publication page or DBLP). He has also authored five books (4 monographs and 1 textbook):


1. S. Mazumder and B. Liu. Lifelong and Continual Learning Dialogue Systems. Springer, February 2024. (First ever book on the topic)
2. Z. Chen and B. Liu. "Lifelong Machine Learning." Morgan & Claypool Publishers. First edition, November 2016; Second edition, August 2018. (First ever book on the topic).
3. B. Liu. “Sentiment Analysis: Mining Opinions, Sentiments, and Emotions.” Cambridge University Press, June 2015. (An Amazon reviewer comment: Bible for sentiment analysis
4. B. Liu. “Sentiment Analysis and Opinion Mining.” Morgan & Claypool Publishers, May, 2012.
5. B. Liu. “Web Data Mining: Exploring Hyperlinks, Contents and Usage Data.” Springer, First Edition, 2006; Second Edition, 2011.


• Research Contributions: He is best known for his pioneering work on sentiment analysis and opinion mining (his KDD-2004 paper essentially opened up the field for research and applications as it defined the main tasks and concepts of the field, and it won the KDD-2015 Test-of-Time award), fake/deceptive opinion detection (his WSDM-2008 paper is the first ever paper on detecting fake information in the social media and it won the WSDM-2019 Test-of-Time award), association rules based classification (his KDD-1998 paper is the first ever paper on using association rules for classification, which won the KDD-2014 Test-of-Time award), and lifelong and continual learning (he wrote the first ever book dedicated to the topic with his student in 2016). Recently, his group made a breakthrough (AAAI-2025) that enables continual learning to achieve its theoretical upper bound accuracy.

  He is also a pioneer researcher of PU learning (learning from positive and unlabeled examples) (or set expansion), Web data extraction and interestingness in data mining.
  

• Awards and Honors (Selected):
  
  1. ACM Fellow, AAAI Fellow, and IEEE Fellow
  2. ACM SIGKDD Innovation Award - the most prestigious technical contribution award from ACM SIGKDD
  3. Test-of-Time Paper Award - Honorable Mention, WSDM-2020: X. Ding, B. Liu and P. Yu. "A holistic lexicon-based approach to opinion mining." Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM-2008), 2008.
  4. Test-of-Time Paper Award, WSDM-2019: N. Jindal and B. Liu “Opinion Spam and Analysis.” Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM-2008), 2008.
  5. Test-of-Time Paper Award, KDD-2015: M. Hu and B. Liu. “Mining and Summarizing Customer Reviews.” Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), 2004.
  6. Test-of-Time Paper Award, KDD-2014: B. Liu, W. Hsu and Y. Ma. “Integrating Classification and Association Rule Mining.” Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-1998), 1998.
  
  
• Press Coverage: His work has also made important sociatal impact. He and his work have been reported widely in popular press and tech news media internationally, including a front-page article in the New York Times.


• Professional Services: He served as the Chair of ACM SIGKDD (7/1/2013 - 6/30/2017). SIGKDD is the premier academic community for data mining, data science, and big data. He has also served as a Program Committee Chair for the flagship data mining conferences of ACM, IEEE and SIAM (KDD, ICDM, and SDM respectively), three other data mining conferences (CIKM, WSDM, and PAKDD), and a lifelong machine learnng conference (CoLLAs), as an associate editor of several leading data mining journals, e.g., TKDE, TWEB, TKDD, DMKD, and as a senior area/track chair or senior program committee member of numerous NLP, AI, machine learning, data mining, and Web technology conferences.

Created on June 15, 2015 by Bing Liu.