Basic Information

I am a fifth-year Ph.D. student in Department of Computer Science and Engineering, The Ohio State University. My advisor is Professor Srinivasan Parthasarathy. My research interest lies in general Data Mining and Machine Learning with a focus on Network Embedding, Outlier Detection, and Graph Mining. Before joining OSU, I got my Bachelor Degree in Computer Science and Engineering from Beihang University in 2013.

Contact

  • Email: liangji AT cse.ohio-state.edu
  • Address: 395 Dreese Laboratory, 2015 Neil Ave, Columbus, OH-43210, USA

Update

  • Tired of slow speed of graph embedding? Try our multi-level framework to speed up your embedding method. (02/2018).
  • Our work of SEANO is accepted by SDM’18. Code and data are available online.(12/2017)
  • Our work of Human-guided Flood Mapping is accepted by WWW’18 (12/2017).
  • Our paper on heterogeneous information networks analysis is accepted by TKDD. (10/2017)
  • I am doing my second internship at Google. (05/2017–08/2017)
  • Our paper on contextual outlier detection is accepted to CIKM’16. (10/2016)
  • I am doing my summer internship at Google. (05/2016–08/2016)
  • Our paper is accepted by WWW’16 for oral presentation. (04/2016)
  • I am now a research scientist intern at Bell Labs. (05/2015–08/2015)
  • The office hour for CSE2331/5331 is 4-5pm Tuesday in DL686. (2015 Spring)

Publications

  • J. Liang, S. Gurukar, S. Parthasarathy. “MILE: A Multi-Level Framework for Scalable Graph Embedding”. arXiv preprint arXiv:1802.09612, 2018. [PDF][Code & Data]
  • J. Liang, P. Jacobs, J. Sun, S. Parthasarathy. “Semi-supervised Embedding in Attributed Networks with Outliers”. To appear in Proceedings of SIAM International Conference on Data Mining (SDM’18), 2018. [PDF][Code & Data][bib]
  • J. Liang, P. Jacobs, S. Parthasarathy. “Human-Guided Flood Mapping: From Experts to the Crowd”. To appear in Proceedings of the Web Conference (WWW’18), 2018. [PDF]
  • J. Liang, D. Ajwani, P. Nicolson, A. Sala, S. Parthasarathy. “Prioritized Relationship Analysis in Heterogeneous Information Networks”. in ACM Transactions on Knowledge Discovery from Data (TKDD), 2018. [PDF][bib]
  • J. Liang and S. Parthasarathy. “Robust Contextual Outlier Detection: Where Context Meets Sparsity”. In Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM’16), 2016. [PDF][Extended Version][bib]
  • J. Liang, D. Ajwani, P. Nicolson, A. Sala, S. Parthasarathy. “What Links Alice and Bob? Matching and Ranking Semantic Patterns in Heterogeneous Networks”. In Proceedings of the 25th International World Wide Web Conferences (WWW’16), pp. 879-889, 2016. [PDF][Slides_Prezi][Dataset][bib]
  • J. Liang, D. Fuhry, D. Maung, A. Borstad, R. Crawfis, L. Gauthier, A. Nandi, S. Parthasarathy. “Data Analytics Framework for A Game-based Rehabilitation System”. In Proceedings of the 6th International Conference on Digital Health (DH’16), pp. 67-76, 2016 [PDF][Slides_PPT][Slides_PDF][bib]
  • Y. Ye, Y. Xu, Y. Zhu, J. Liang, T. Lan, M. Yu. “The Characteristics of Moral Emotions of Chinese Netizens towards an Anthropogenic Hazard: A Sentiment Analysis on Weibo”. In Acta Psychologica Sinica, 2016.
  • Y. Ruan, D. Fuhry, J. Liang, Y. Wang, and S. Parthasarathy. “Community Discovery: Simple and Scalable Approaches”. In User Community Discovery , pp. 23-54. Springer International Publishing, 2015. [link][bib]

Professional Services

  • CIKM 2017, Program Committee Member
  • WWW 2017, Program Committee Member
  • ACM Transactions on Knowledge Discovery from Data (TKDD), Reviewer
  • Data Mining and Knowledge Discovery (DMKD), Reviewer
  • IEEE/ACM Transactions on Networking (ToN), Reviewer
  • IEEE Transactions on Systems, Man, and Cybernetics: Systems, Reviewer