651 61885

KAN Min Yen

Associate Professor
Vice Dean, Undergraduate Studies

  • Ph.D. (Computer Science, Columbia University, 2002)
  • M.Sc. (Computer Science, Columbia University, 1998)
  • B.S. (Computer Science, Columbia University, 1996)

Min-Yen Kan (BS;MS;PhD Columbia Univ.; SACM, SIEEE) is an Associate Professor and Vice Dean of Undergraduate Studies at the National University of Singapore. Min is an active member of the Association of Computational Linguistics (ACL), currently serving as a co-chair for the ACL Ethics Committee, and previously as the ACL Anthology Director (2008–2018). He is an associate editor for Information Retrieval and the survey editor for the Journal of AI Research (JAIR). His research interests include digital libraries, natural language processing and information retrieval. He was recognized as a distinguished speaker by the ACM for natural language processing and digital libraries research. Specific projects include work in the areas of scientific discourse analysis, fact verification, full-text literature mining, lexical semantics and large language models. He leads the Web Information Retrieval / Natural Language Processing Group (WING.NUS)


Artificial Intelligence
  • Machine Learning
  • Natural Language Processing
  • Natural Language Processing
  • Multimedia Search & Recommendation
  • Social Media Analysis


  • Natural Language Processing

  • Large Language Models

  • Digital Libraries

  • Information Retrieval

  • Applied Machine Learning

  • Human-Computer Interaction

  • Web and Networked Information Systems


Scholarly Document Information Extraction

Particular components of scholarly documents have different uses and can be extracted and analysed to help improve the speed and quality of scientific discovery. These include better understanding of the topics, problems, approaches, evaluation metrics, tools and datasets used in research. Extracting such data from natural language text allows computational analyses of works at a large scale.


Task Oriented Dialogue Systems

We now use voice- and text-enabled chatbots and dialogue systems often to accomplish tasks. We examine ways to improve such systems by incorporating everyday knowledge in the form of knowledge graphs and incorporating means to adapt trained systems to new domain application areas.


Recommendation Systems

Recommendations Systems curate our news feeds, and show products for us to buy, shows to watch and music to listen to. Our work examines the use of temporal and prerequisite constraints in improving recommendation systems quality in sparse data application areas, such as module and course recommendation.


Towards Controllable Generation for Scientific Document Summarization

This project enhances scientific document summarization by using scientific claims as constraints, improving summarization quality and user control. It integrates claim representation into seq2seq models like BART and T5, aiming for topic-based evaluation and plans to publish three works and deliver a practical toolkit.


Web, Information Retrieval, Natural Language Processing Group (WING)

Min leads WING, a group of postgraduate and undergraduate researchers examining issues in digital libraries, information retrieval and natural language processing research. Find out more at


Student Submission Integrity Diagnosis (SSID)

SSID is an instructor-centric source code plagiarism detection system (i.e., for programming assignments). It aims to streamline the checking process and helps instructors manage plagiarism detection workflows.


  • Kishaloy Halder, Lahari Poddar and Min-Yen Kan 2017 Modeling Temporal Progression of Emotional Status in Mental Health Forum: A Recurrent Neural Net Approach. In Proceedings of 8th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis WASSA '17. September 2017. Copenhagen, Denmark.
  • Wenqiang Lei, Xuancong Wang, Meichun Liu, Ilija Ilievski, Xiangnan He and Min-Yen Kan 2017 SWIM: A Simple Word Interaction Model for Implicit Discourse Relation Recognition. In Proceedings of the International Joint Conference on Artificial Intelligence IJCAI '17, August 2017, Melbourne, Australia.
  • Muthu Kumar Chandrasekaran, Carrie Demmans Epp, Min-Yen Kan and Diane Litman 2017. Using Discourse Signals for Robust Instructor Intervention Prediction. In Proceedings of the Thirty-First AAAI conference on Artificial Intelligence AAAI-17, San Francisco, USA, 3415-3421, AAAI.
  • Tao Chen, Xiangnan He and Min-Yen Kan 2016. Context-aware Image Tweet Modelling and Recommendation. In Proceedings of the 24th ACM International Conference on Multimedia MM'16, Amsterdam, The Netherlands. 15-19 Oct.
  • Xiangnan He, Hanwang Zhang, Min-Yen Kan and Tat-Seng Chua 2016.Fast Matrix Factorization for Online Recommendation with Implicit Feedback. In Proceedings of Special Interest Group on Information Retrieval SIGIR '16. Pisa, Italy. July 17-21.
  • Bang Hui Lim, Dongyuan Lu, Tao Chen and Min-Yen Kan 2015.#mytweet via Instagram: Exploring User Behaviour across Multiple Social Networks. In Proceedings of IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ASONAM '15, Paris, France.
  • Tao Chen, Naijia Zheng, Yue Zhao, Muthu Kumar Chandrasekaran, Min-Yen Kan 2015. Interactive Second Language Learning from News Websites. In Proceedings of 2nd Workshop on Natural Language Processing Techniques for Educational Applications NLP-TEA '15, Beijing, China.
  • Muthu Kumar Chandrasekaran, Min-Yen Kan, Kiruthika Ragupathi and Bernard C. Y. Tan 2015. Learning instructor intervention from MOOCforums: Early Results and Issues. In Proceedings of Education Data Mining EDM '15, Madrid, Spain.


  • Best Paper Award, 2019, Conference on Information and Knowledge Management (CIKM 2019)

  • Distinguished Service Awards, Association of Computational Linguistics

  • Vannevar Bush Best Paper Award, 2012, Joint Conference on Digital Libraries (JCDL 2012)

  • 1st place in automated ROUGE measures among all teams, TAC 2011 Guided Summarization task, Text Analysis Conference

  • Senior Member ACM


Natural Language Processing


In the News

8 February 2024
Associate Professor Kan Min Yen emphasises that Southeast Asia's regulations are less detailed compared to the EU's, citing the region's ...
5 February 2024
Associate Professor Kan Min Yen asserts that ASEAN, as a “critical region,” stands to gain from suitable AI adoption and implementation. However, he highlights ...
26 January 2024
10 December 2023
In the race to harness the power of artificial intelligence (AI), Singapore aims to get ahead by more than tripling ...


1 July 2021
There have been many moments of disbelief throughout the pandemic, but one of the most shocking ones happened last April, ...