Haokai Lu




Howdy! I recently obtained my Ph.D. in the Computer Science & Engineering Department at Texas A&M University, advised by Prof. James Caverlee. I'm broadly interested in applied machine learning and developing computational methods for better understanding of human behaviors in social media.
Previously, I was at the Computer Engineering & Systems Group and worked with Prof. Peng Li. I obtained my Bachelor's degree from Southeast University in China before coming to TAMU.
I am now working at Google as a software engineer.

Publications

  • Learning Geo-Social User Topical Profiles with Bayesian Hierarchical User Factorization. SIGIR, 2018. (acceptance rate: 21%) [pdf]
    H. Lu, W. Niu and J. Caverlee.

  • Neural Personalized Ranking for Image Recommendation. WSDM, 2018. (acceptance rate: 16%) [pdf]
    W. Niu, J. Caverlee and H. Lu.

  • Location-Sensitive User Profiling Using Crowdsourced Labels. AAAI, 2018. (acceptance rate: 25%) [pdf]
    W. Niu, J. Caverlee and H. Lu.

  • What Are You Known For? Learning User Topical Profiles with Implicit and Explicit Footprints. SIGIR, 2017. (acceptance rate: 22%) [pdf]
    C. Cao, H. Ge, H. Lu, X. Hu and J. Caverlee.

  • Discovering What You're Known For: A Contextual Poisson Factorization Approach. RecSys, 2016. (acceptance rate: 18%) [pdf]
    H. Lu, J. Caverlee and W. Niu.

  • TAPER: A Contextual Tensor-Based Approach for Personalized Expert Recommendation. RecSys, 2016. (best paper nominee) [pdf]
    H. Ge, J. Caverlee and H. Lu.

  • Community-Based Geospatial Tag Estimation. ASONAM, 2016. (acceptance rate: 14%) [pdf]
    W. Niu, J. Caverlee, H. Lu and K. Kamath.

  • BiasWatch: A Lightweight System for Discovering and Tracking Topic-Sensitive Opinion Bias in Social Media. CIKM, 2015. (acceptance rate: 18%) [pdf]
    H. Lu, J. Caverlee and W. Niu.

  • Exploiting Geo-Spatial Preference for Personalized Expert Recommendation. RecSys, 2015. (acceptance rate: 21%) [pdf]
    H. Lu and J. Caverlee.

  • Linking brain behavior to underlying cellular mechanisms via large-scale brain modeling and simulation. Neurocomputing, 2012. [pdf]
    Y. Zhang, B. Yan, M. Wang, J. Hu, H. Lu and P. Li.

  • Stochastic projective methods for simulating stiff chemical reacting systems. Computer Physics Communications, 2012. [pdf]
    H. Lu and P. Li.

Industry Experience

  • Software engineering intern, Adwords Express quality team, Google, Mountain View, USA, May 2016 - Aug 2016.
    Area: deep learning, multi-class classification
    Project: exploring deep neural networks for Adwords Express keyword prediction.

Teaching

Technical Talks

  • Discovering What You're Known For: A Contextual Poisson Factorization Approach. RecSys, Boston, 2016.
  • BiasWatch: A Lightweight System for Discovering and Tracking Topic-Sensitive Opinion Bias in Social Media. CIKM, Melbourne, 2015.
  • Exploiting Geo-Spatial Preference for Personalized Expert Recommendation. RecSys, Vienna, 2015.

Professional Services

  • Journal Reviewer: Transactions on Knowledge and Data Engineering, ACM Transactions on Service Computing
  • Conference Reviewer: ASONAM'16
  • External Reviewer: WWW'(16, 15), WSDM'(18, 17, 16), KDD'(16, 15), SIGIR'15, ICWSM'15, SDM'15, IJCAI'15, ICDM'14