Jingrui He Assistant Professor Computer Science Department Stevens Institute of Technology Hoboken, N.J. 10598 Phone:    201-216-5358 Fax: 201-216-8249 Email:     Jingrui dot He at stevens dot edu C.V.
Research Interest My research interest is mainly in statistical machine learning and large scale data mining. On the algorithmic side, I mainly focus on the heterogeneous machine learning and rare category analysis. On the application side, I am interested in social network analysis, public safety, traffic analytics, multimedia, and virtual metrology in semiconductor manufacturing.
Selected Publications. Complete List (DBLP | Google Scolar)
1. Dan Zhang, Jingrui He, Luo Si, Richard D. Lawrence: MILEAGE: Multiple Instance LEArning with Global Embedding. ICML (3) 2013: 82-90 2. Dan Zhang, Jingrui He, Richard D. Lawrence: MI2LS: multi-instance learning from multiple informationsources. KDD 2013: 149-157 3. Jingrui He, Yada Zhu: Hierarchical Multi-task Learning with Application to Wafer Quality Prediction. ICDM 2012: 290-298 4. Jingrui He, Hanghang Tong, Qiaozhu Mei, Boleslaw K. Szymanski: GenDeR: A Generic Diversified Ranking Algorithm. NIPS 2012: 1151-1159 5. Jingrui He. Analysis of Rare Categories. Springer-Verlag New York, LLC, November 2011. ISBN 978-3-642-22812-4. [Book] [Video] 6. Jingrui He and Rick Lawrence. A Graph-based Framework for Multi-Task Multi-View Learning. Int. Conf. on Machine Learning (ICML), 2011 [PDF] [Video] 7. Hanghang Tong, Jingrui He, Zhen Wen, and Ching-Yung Lin. Diversified Ranking on Large Graphs: an Optimization Viewpoint. ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD), 2011. 8. Dan Zhang, Jingrui He, Yan Liu, Luo Si, and Rick Lawrence. Multi-View Transfer Learning with a Large Margin Approach. ACM SIGKDD Conf. on Knowledge Discovery and Data Mining (KDD), 2011. 9. Jingrui He, Hanghang Tong, and Jaime Carbonell. Rare Category Characterization. IEEE Int. Conf. on Data Mining (ICDM), 2010. [Invited to FCS SI on ‘Best of ICDM2010’] 10. Jingrui He, and Jaime Carbonell. Co-Selection of Features and Instances for Unsupervised Rare Category Analysis. SIAM Int. Conf. on Data Mining (SDM), 2010. [Invited to SAM SI on ‘Best of SDM10’] 11. Jingrui He, Yan Liu, and Richard Lawrence. Graph-based Transfer Learning. ACM Conf. on Information and Knowledge Management (CIKM), 2009. 12. Jingrui He, and Jaime Carbonell. Prior-Free Rare Category Detection. SIAM Int. Conf. on Data Mining (SDM), 2009. 13. Jingrui He, Yan Liu, and Richard Lawrence. Graph-based Rare Category Detection. IEEE Int. Conf. on Data Mining (ICDM), 2008. 14. Jingrui He, and Jaime Carbonell. Nearest-Neighbor-Based Active Learning for Rare Category Detection. Neural Information Processing Systems (NIPS), 2007 15. Jingrui He, Mingjing Li, Hong-Jiang Zhang, Hanghang Tong, and Changshui Zhang. Manifold-Ranking Based Image Retrieval. ACM Int. Conf. on Multimedia (MM), 2004