My research interest is in the broad area of machine learning. The focus of my doctoral work is on latent variable discovery and topic modeling.





  • W. Ding, P. Ishwar, and V. Saligrama, “A Topic Modeling Approach to Rank Aggregation,”  in Advances in Neural Information Processing Systems (NIPS’14), Workshop on Analysis of Rank Data: Confluence of Social Choice, Operations Research, and Machine Learning, Montreal, Canada, 13, Dec., 2014. [Best Student Paper Award] [arXiv version]
  • W. Ding, M. H. Rohban, P. Ishwar, and V. Saligrama, “Efficient Distributed Topic Modeling with Provable Guarantees,” in Proc. International Conference on Artificial Intelligence and Statistics (AISTATS’14),  Reykjavik, Iceland, 22-25, Apr., 2014, JMLR W&CP 33 :167-175
  • W. Ding, P. Ishwar, V. Saligrama, and W. C. Karl, “Sensing-Aware Kernel SVM,” in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP’14), Florence, Italy, 4-9 May, 2014. [arXiv version]