Kai Zhang (张凯)

Kai Zhang's picture 

Associate Professor
Department of Computer and Information Sciences
Temple University, Philadelphia
1925 N. 12th Street, Philadelphia PA
Email: zhang.kai@temple.edu
Phone +1 (215)-204-8455

I'm looking for Ph.D. students and visiting scholars who are interested in machine learning, big data analytics, time series analysis and brain functional networks. Feel free to contact me if you are interested in working with me.

Regularly Updated CV

Curriculum vitae.


  • ACM SIGKDD 2016 Best Paper Runner-up Award.

  • NEC 2016 Business Contribution Awards.

  • 2006 IEEE Hong Kong Chapter of Signal Processing Postgraduate Forum Best Paper Award.

News and Updates

  • Mar 2018: One paper Neural and Genetic Determinants of Creativity” has been accepted by NeuroImage. Preprint can be found here.
  • Dec 2017: Our paper A distributed Algorithm for Tensor Completion on Spark” has been accepted by the International Conference on Data Engineering (ICDE 2018).
  • Dec 2017: Our paper Mining higher-order network structures via motif-vertex-interactions” has been accepted by the Europhysics Letters (EPL 2018).
  • Dec 2017: Our paper Network Inference from Contrastive Groups Using Discriminative Structural Regularization” has been accepted by SIAM Conference of Data Mining (SDM 2018).
  • Dec 2017: Our paper “Scaling up Kernel SVM on Limited Resources: A Low-rank Linearization Approach” has been conditionally accepted by the IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2018)
  • Nov 2017: Our paper “A Feature Sampling Strategy for Analysis of High Dimensional Genomic Data” has been accepted by the IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB 2018).
  • Oct 2017: Our paper “Substructure Assembling Network for Graph Classification” has been accepted by the 32th AAAI Conference on Artificial Intelligence (AAAI 2018).
  • Oct 2017: Our paper “Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems” was accepted by the IEEE International Conference on Data Mining series (ICDM 2017).
  • Sep 2017: Our paper “Efficient Discovery of Abnormal Event Sequences in Enterprise Security Systems” was accepted by 26th ACM International Conference on Information and Knowledge Management (CIKM 2017).
  • Aug 2017: I gave a presentation on our recent work “Randomization or Condensation?: Linear Cost Matrix Sketching Via Cascaded Compression Sampling” in the 23rd ACM SIGKDD Conference held in Halifax, Canada.


  • Aug 2017: Our paper “Low-rank Decomposition Meets Kernel Learning: A Generalized Nyström Method” was accepted by the Artificial Intelligence.
  • Aug 2016: Our paper “Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations” won the KDD 2016 Best Paper Runner-up Award.
  • Aug 2016: Our paper “Annealed Sparsity via Adaptive and Dynamic Shrinking” was accepted by the 2016 ACM SIGKDD Conference.
  • Aug 2016: Our paper “Neural, electrophsiological and anatomical basis of brain network variability and its characteristic changes in mental disorders” was accepted in Brain August issue and selected as editor’s choice and cover page.