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Dr. Jing Li

Research Scientist, Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates.

Email: jli030@e.ntu.edu.sg or jing.li@inceptioniai.org


About Me

Dr. Jing Li is currently a Research Scientist at the Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, United Arab Emirates. Prior to that, he was a Research Fellow in the School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore. He obtained his PhD degree in Computer Science, at NTU, Singapore, under the supervision of Prof. Aixin Sun and Prof. Zhenchang Xing in 2018. He received his B.E. and M.E. in Electrical Engineering from University of Electronic Science and Technology of China (UESTC), China, in 2010 and 2013, respectively. His research aims to build up semantic Web systems to support information needs of web users via deep text understanding, information extraction, machine intelligent question answering, knowledge representation, as well as social media analysis.

Research Interests
  • Information Retrieval / Natural Language Processing
    • Question answering based on deep learning
    • Semantic search
    • Named entity recognition
    • Knowledge graph
    • Software API documentation mining
  • Machine Learning
    • Transfer learning
    • Meta-learning
  What's New
  Jan, 2020
One paper in WWW 2020.
  Nov, 2019
One paper in AAAI 2020.
  Aug, 2019
One paper in EMNLP 2019.
  July, 2019
  May, 2019
One paper in IJCAI 2019.
  Dec, 2018
Write up a survey: Deep Learning for NER
  Dec, 2018
I will join IIAI, as a Research Scientist.
  Jun, 2018
One paper is accepted by WWWJ.
  May, 2018
One paper is accepted by JASIST.
  Apr, 2018
One paper is accepted by IJCAI 2018.
Selected Publications [Full List]

Submitted

  • A Survey on Deep Learning for Named Entity Recognition
    Jing Li, Aixin Sun, Jianglei Han and Chenliang Li
    Under review   arXiv   BibTex
  • Neural Text Segmentation and Its Application to Sentiment Analysis
    Jing Li, Billy Chiu and Ling Shao
    Under review   SegBot
  • Neural Named Entity Boundary Detection
    Jing Li, Aixin Sun and Yukun Ma
    Under review   BdryBot
  • Named Entity Boundary Detection via Meta-Learning
    Jing Li
    Under review
  • Few-Shot Named Entity Recognition
    Jing Li
    Under review
  • 2020

    MetaNER: Named Entity Recognition with Meta-Learning
    Jing Li, Shuo Shang and Ling Shao
    WWW-20- The Web Conference, 2020. Acceptance rate: 217/1129 (19.2%).

    2019

    Adversarial Transfer for Named Entity Boundary Detection with Pointer Networks
    Jing Li, Deheng Ye and Shuo Shang
    IJCAI-19- The 28th International Joint Conference on Artificial Intelligence, Pages 5053-5069, 2019. Acceptance rate: 850/4752 (17.9%). PDF
    Neural Discourse Segmentation
    Jing Li
    IJCAI-19- The 28th International Joint Conference on Artificial Intelligence, Pages 6539-6541, 2019. (Demo) PDF
  • LinkLive: Discovering web learning resources for developers from Q&A discussions
    Jing Li, Zhenchang Xing and Aixin Sun
    WWWJ-19- World Wide Web. 22(4), Pages 1699-1725, Springer, 2019. (IF: 1.770) PDF
  • 2018

  • To Do or Not To Do: Distill Crowdsourced Negative Caveats to Augment API Documentation
    Jing Li, Aixin Sun and Zhenchang Xing
    JASIST-18- Journal of the Association for Information Science and Technology. Volume 69, Issue 12, Pages 1460-1475, Wiley, 2018. (IF: 2.738) PDF
  • SegBot: A Generic Neural Text Segmentation Model with Pointer Network
    Jing Li, Aixin Sun and Shafiq Joty
    IJCAI-18-The 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence. Pages 4166-4172, 2018. Acceptance rate: 710/3470 (20.5%). PDF   Website
    API Caveat Explorer: Surfacing Nagative Usages from Practice
    Jing Li, Aixin Sun, Zhenchang Xing and Lei Han
    SIGIR-18-The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, Pages 1293-1296. ACM, 2018. (Demo)   Website PDF
  • Learning to Answer Programming Questions with Software Documentation through Social Context Embedding
    Jing Li, Aixin Sun and Zhenchang Xing
    INS-18- Information Sciences. Volumes 448–449, Pages 36-52, June 2018, Elsevier. (IF: 5.524) PDF
  • Leveraging Official Content and Social Context to Recommend Software Documentation
    Jing Li, Zhenchang Xing and Ashad Kabir
    IEEE TSC-18- IEEE Transactions on Services Computing. IEEE, 2018. (IF: 5.707) PDF
  • 2016

    From Discussion to Wisdom: Web Resource Recommendation  for Hyperlinks in Stack Overflow
    Jing Li, Zhenchang Xing, Deheng Ye and Xuejiao Zhao
    SAC-16-The 31st ACM Symposium on Applied Computing,2016. Acceptance rate: 252/1047 (24.07%). PDF
    BPMiner: Mining Developers' Behavior Patterns from Screen-Captured Task Videos
    Jing Li, Lingfeng Bao, Zhenchang Xing, Xinyu Wang and Bo Zhou
    SAC-16-The 31st ACM Symposium on Applied Computing,2016. Acceptance rate: 252/1047 (24.07%). PDF

    Before 2015


  • Applications of Compressed Sensing for Multiple Transmitters Multiple Azimuth Beams SAR Imaging
    Jing Li, Shunsheng Zhang,Junfei Chang
    PIER-12- Progress In Electromagnetics Research, Vol. 127, Pages 259–275, 2012. (IF: 2.322) PDF
  • Forward-Looking Bistatic SAR Imaging Based On High Order Range Equation And High Order Phase Compensation
    Shunsheng Zhang and Jing Li*
    JEWA-12- Journal of Electromagnetic Waves and Applications, vol.26, nos.17-18, pages 2304-2314, 2012. (IF: 1.351) PDF *Corresponding author
  • Professional Services
    • Conference PC Members
      • The International Joint Conference on Artificial Intelligence (IJCAI 2020)
      • The ACM International Conference on Information and Knowledge Management (CIKM 2019)
      • The Asia Information Retrieval Societies Conference (AIRS 2019)
    • Journal Reviewers
      • IEEE Journal on Selected Areas in Communications (JSAC)
      • IEEE Transactions on Knowledge and Data Engineering (TKDE)
      • Elsevier, Neurocomputing
      • Wiley, Journal of the Association for Information Science and Technology (JASIST)
      • Springer, Knowledge and Information Systems (KAIS)
      • IEEE Access