Jundong Li [CV]

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PhD Student
Data Mining and Machine Learning Laboratory
School of Computing, Informatics, and Decision Systems Engineering
Arizona State University

Email: jundong.li at asu dot edu

Personal Information

I am a 4th year PhD student of Computing Science and Engineering, Arizona State University. I work as a research assistant at Data Mining and Machine Learning Laboratory, my advisor is Professor Huan Liu.

Before that, I obatained BEng degree from College of Computer Science and Technology, Zhejiang University in 2012 and MSc degree from Department of Computing Science, University of Alberta in 2014. My advisor was Professor Osmar R. Zaïane at University of Alberta. I was interning in Yahoo! Research at Sunnyvale, CA in 2016 Summer.

Research Interest

My research interest is generally in data mining and machine learning and their applications in social media.

What's New

  • [2017/11] One journal paper accepted by ACM TIST.
  • [2017/11] Two conference papers accepted by AAAI 2018, see you in New Orleans.
  • [2017/11] Attended CIKM 2017 in Singapore and gave a paper presentation.
  • [2017/10] Two conference papers accepted by WSDM 2018, see you in Los Angeles.
  • [2017/09] Attended ECML-PKDD 2017 in Skopje, Macedonia and gave a paper presentation.
  • [2017/08] Received CIKM 2017 Student Travel Award from NSF and SIGWEB.
  • [2017/08] One journal paper accpted by ACM Computing Surveys.
  • [2017/08] Attended IJCAI 2017 in Melbourne, Australia and gave two paper presentations.
  • [2017/08] Presented a tutorial in KDD 2017 on "Recent advances in feature selection: a data perspective".
  • [2017/08] Attended KDD 2017 in Halifax, Canada and presented a poster paper.
  • Software

    We release an open-source feature selection repository (sickit-feature):
    Project Webpage
    Technical Survey Paper
    Github Link

    News and Blog Coverage:
    scikit-feature: Open-Source Feature Selection Repository in Python
    5 Machine Learning Projects You Can No Longer Overlook
    Pulse: The Starting Point for Feature Selection
    What is Dim Reduction & Feature Selection

    Publications [Google Scholar] [DBLP]

    Preprints:

    1. Understanding and Predicting Delay in Reciprocal Relations [A Preprint from arXiv] [bib]
      Jundong Li, Jiliang Tang, Yilin Wang, Yali Wan, Yi Chang and Huan Liu

    Tutorials:

    Book Chapters:

    Journal Papers:

    1. Feature Selection: A Data Perspective [pdf] [bib]
      Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang and Huan Liu
      ACM Computing Surveys (CSUR), 2017 (To Appear)

    2. Exploiting Multi-Label Information for Noise Resilient Feature Selection [pdf] [bib]
      Ling Jian, Jundong Li and Huan Liu
      ACM Transactions on Intelligent Systems and Technology (TIST), 2017 (To Appear)

    3. Toward Online Node Classification on Streaming Networks [pdf] [bib]
      Ling Jian, Jundong Li and Huan Liu
      Data Mining and Knowledge Discovery (DMKD), 2017 (To Appear)

    4. Exploiting Expertise Rules for Statistical Data-Driven Modeling [pdf] [bib]
      Ling Jian, Jundong Li and Shihua Luo
      IEEE Transactions on Industrial Electronics (TIE), 64(11): 8647-8656, 2017

    5. Challenges of Feature Selection for Big Data Analytics [pdf] [bib]
      Jundong Li and Huan Liu
      IEEE Intelligent System, 32(2): 9-15, 2017

    6. Budget Online Learning Algorithm for Least Squares SVM [pdf] [bib]
      Ling Jian, Shuqian Shen, Jundong Li, Xijun Liang and Lei Li
      IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 28(9): 2076-2087, 2017

    7. Exploiting Statistically Significant Dependent Rules for Associative Classification [pdf] [bib]
      Jundong Li and Osmar R. Zaïane
      Intelligent Data Analysis: An International Journal, 21(5): 1155-1172, 2017

    8. On Discovering Co-Location Patterns in Datasets: A Case Study of Pollutants and Child Cancers [pdf] [bib]
      Jundong Li, Aibek Adilmagambetov, M. Shazan M. Jabbar, Osmar R. Zaïane, Alvaro Osornio-Vargas and Osnat Wine
      GeoInformatica, 20(4): 651-692, 2016

    Conference Papers:

    2018:

    1. Unsupervised Personalized Feature Selection [pdf] [bib]
      Jundong Li, Liang Wu, Harsh Dani, Huan Liu
      In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), New Orleans, LA, USA, Feb 2-7, 2018

    2. Personalized Privacy-Preserving Social Recommendation [pdf] [bib]
      Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang
      In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), New Orleans, LA, USA, Feb 2-7, 2018

    3. Streaming Link Prediction on Dynamic Attributed Networks [pdf] [bib]
      Jundong Li, Kewei Cheng, Liang Wu, Huan Liu
      In Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), Los Angeles, Carlifornia, Feb 5-9, 2018

    4. Exploring Expert Cognition for Attributed Network Embedding [pdf] [bib]
      Xiao Huang, Qingquan Song, Jundong Li, Xia Hu
      In Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), Los Angeles, Carlifornia, Feb 5-9, 2018

    2017:

    1. Attributed Network Embedding for Learning in a Dynamic Environment [pdf] [bib]
      Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang and Huan Liu
      In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM), Pan Pacific Singapore, Nov 6-10, 2017

    2. Sentiment Informed Cyberbullying Detection in Social Media [pdf] [bib]
      Harsh Dani, Jundong Li and Huan Liu
      In Proceedings of the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Skopje, Macedonia, Sept 18-22, 2017

    3. Radar: Residual Analysis for Anomaly Detection in Attributed Networks [pdf] [bib] [code]
      Jundong Li, Harsh Dani, Xia Hu and Huan Liu
      In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, Aug 19-25, 2017

    4. Reconstruction-based Unsupervised Feature Selection: An Embedded Approach [pdf] [bib]
      Jundong Li, Jiliang Tang and Huan Liu
      In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, Aug 19-25, 2017

    5. Unsupervised Feature Selection in Signed Social Networks [pdf] [bib] [video]
      Jundong Li*, Kewei Cheng*, and Huan Liu (* equal contribution)
      In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), Halifax, Canada, Aug 13-17, 2017

    6. Toward Personalized Relational Learning [pdf] [bib]
      Jundong Li, Liang Wu, Osmar R. Zaïane and Huan Liu
      In Proceedings of the 17th SIAM International Conference on Data Mining (SDM), Houston, Texas, USA, Apr 27-29, 2017

    7. Gleaning Wisdom From The Past: Early Detection of Emerging Rumors in Social Media [pdf] [bib]
      Liang Wu, Jundong Li, Xia Hu and Huan Liu
      In Proceedings of the 17th SIAM International Conference on Data Mining (SDM), Houston, Texas, USA, Apr 27-29, 2017

    8. Accelerated Attributed Network Embedding [pdf] [bib] [code]
      Xiao Huang, Jundong Li and Xia Hu
      In Proceedings of the 17th SIAM International Conference on Data Mining (SDM), Houston, Texas, USA, Apr 27-29, 2017

    9. Understanding and Discovering Deliberate Self-harm Content in Social Media [pdf] [bib]
      Yilin Wang, Jiliang Tang, Jundong Li, Baoxin Li, Yali Wan, Clayton Mellina, Neil O'Hare and Yi Chang
      In Proceedings of the 26th International World Wide Web Conference (WWW), Perth, Australia, Apr 3-7, 2017

    10. Unsupervised Sentiment Analysis with Signed Social Networks [pdf] [bib]
      Kewei Cheng, Jundong Li, Jiliang Tang and Huan Liu
      In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, USA, Feb 4-9, 2017

    11. Label Informed Attributed Network Embedding [pdf] [bib] [code]
      Xiao Huang, Jundong Li and Xia Hu
      In Proceedings of the 10th ACM International Conference on Web Search and Data Mining (WSDM), Cambridge, UK, Feb 6-10, 2017

    2016:

    1. Toward Time-Evolving Feature Selection on Dynamic Networks [pdf] [bib]
      Jundong Li, Xia Hu, Ling Jian and Huan Liu
      In Proceedings of the 16th IEEE International Conference on Data Mining (ICDM), Barcelona, Spain, Dec 12-15, 2016

    2. FeatureMiner: A Tool for Interactive Feature Selection (demo paper) [pdf] [bib] [demo]
      Kewei Cheng, Jundong Li and Huan Liu
      In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM), Indianapolis, USA, Oct 24-28, 2016

    3. Multi-Label Informed Feature Selection [pdf] [bib] [slides] [code]
      Jundong Li*, Ling Jian*, Kai Shu and Huan Liu (* equal contribution)
      In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York, NY, USA, July 9-15, 2016

    4. Robust Unsupervised Feature Selection on Networked Data [pdf] [bib] [slides] [code]
      Jundong Li, Xia Hu, Liang Wu and Huan Liu
      In Proceedings of the 16th SIAM International Conference on Data Mining (SDM), Miami, Florida, USA, May 5-7, 2016

    2015:

    1. Unsupervised Streaming Feature Selection in Social Media [pdf] [bib] [slides]
      Jundong Li, Xia Hu, Jiliang Tang and Huan Liu
      In Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM), Melbourne, Australia, Oct 19-23, 2015

    2. Associative Classification with Statistically Significant Positive and Negative Rules [pdf] [bib]
      Jundong Li and Osmar R. Zaïane
      In Proceedings of the 24th ACM International Conference on Information and Knowledge Management (CIKM), Melbourne, Australia, Oct 19-23, 2015

    2014:

    1. Discovering Statistically Significant Co-location Rules in Datasets with Extended Spatial Objects [pdf] [bib]
      Jundong Li, Osmar R. Zaïane and Alvaro Osornio-Vargas
      In Proceedings of the 16th International Conference on Data Warehousing and Knowledge Discovery (DaWaK), Munich, Germany, Sep 2-4, 2014

    2. Active Learning Strategies for Semi-Supervised DBSCAN [pdf] [bib]
      Jundong Li, Jörg Sander, Ricardo G.J.B Campello and Arthur Zimek.
      In Proceedings of the 27th Canadian Conference on Artificial Intelligence (AI), Montreal, Canada, May 6-9, 2014

    Services

    Conference Program Committee: Journal Reviewer: Conference External Reviewer: