Basic Information

I now work at Google Brain on applied ML research. My focus areas are Recommender Systems, Ads Quality Modeling, Self-Supervised Learning, User Modeling, and Graph Neural Networks. Before this, I received my Ph.D. in Department of Computer Science and Engineering, The Ohio State University, working with Professor Srinivasan Parthasarathy. My Ph.D. research lies in general Data Mining and Machine Learning with a focus on Graph Neural Network/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: liang.albert AT outlook.com liangji AT cse.ohio-state.edu.
  • Address: 1600 Amphitheatre Parkway, Mountain View, CA, 94043

Update

  • I join Google and work with a ML research team (06/2018).
  • I have finished my PhD at Ohio State :) (05/2018).
  • Tired of slow speed of graph embedding? Try our multi-level framework to speed up your embedding method. Code available here. (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”. In ICWSM’21. [PDF][Code & Data][bib]
  • J. Sun, B. Bandyopadhyay, A. Bashizade, J. Liang, P. Sadayappan, S. Parthasarathy. “ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation”. In AAAI’19 [pdf]
  • J. Liang, P. Jacobs, J. Sun, S. Parthasarathy. “Semi-supervised Embedding in Attributed Networks with Outliers”. 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”. 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

Conferences

  • AAAI 2019/2020/2021/2022, Program Committee Member
  • WSDM 2021/2022, Program Committee Member
  • KDD 2021/2022, Program Committee Member
  • SIGIR 2020/2021/2022, Program Committee Member
  • SIGMOD 2021, Program Committee Member
  • CIKM 2017, Program Committee Member
  • WWW 2017, Program Committee Member

Journals

  • IEEE Transactions on Knowledge and Data Engineering (TKDE), Reviewer
  • 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

Useful Links