Shandian Zhe

Abount Me

I am currently a student in PhD program in Computer Science Department of Purdue University. My advisor is Prof. Jennifer Neville.

My resaerch interests mainly lie in Bayesian machine learning and its applicaiton in data science. In more detail, I focus on two topics: Bayesian sparse learning and nonparametrics. For sparse learning, I develop scalable inference algorithms for Bayesian spike-and-slab models and apply them for high-dimensional feature selection and online click-through-rate prediction; I design novel Bayesian sparse group selection models for pathway based genomic data analysis, and multiview learning models for association study in Alzheimer's disease. For Bayesian nonparametrics, I use Gaussian processes and Dirichlet processes to analyze multidimensional array data, i.e., tensors, to capture complicated relationships and hidden clusters. To handle real-world large tensor data, I derive tractable and tight variational evidence lower bounds, based on which I develop distributed or online approximate inference algorithms.

Email: szhe at
Office: Computer Science Department, Lawson 2149-21
Address: Lawson 2149-22, 305 N. University Street, West Lafayette, IN 47907-2107

Curriculum Vitae


  • AAAI/SIGAI 2017 Doctoral Consortium Scholarship
  • Google PhD Fellowship for Machine Learning 2016
  • AAAI 2015 Outstanding Student Paper Honorable Mention
  • Pacific Symposium on Biocomputing 2014 travel award
  • Publications

    Source Code

    Working Experience

  • Yahoo! Ad Science and Data team, 05/2016-08/2016
  • Yahoo! Labs, 05/2015-08/2015
  • NEC Laboratories America, INC. 05/2014-08/2014
  • Professional Serverices

  • Reviewer for International Conference for Machine Learning (ICML) 2014, 2015
  • Reviewer for Neural Information Processing Systems (NIPS) 2015, 2016, 2017
  • Reviewer for Journal of Machine Learning Research (JMLR)
  • Reviewer for IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • Reviewer for IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • Program Committee member for The 2nd International Conference on Data Analytics, 2013
  • Program Committee member for The 2nd Workshop on Scalable Machine Learning: Theory and Applications, IEEE International Conference on Big Data, 2014
  • Program Committee member for The Third IEEE International Conference on Multimedia Big Data, 2017
  • Program Committee member for KDD 2017 workshop on AdKDD and TargetAD