Dr. Sheng Chen received the B.S. and M.S. degrees in control science and engineering from the Huazhong University of Science and Technology, Wuhan, China, in 2004 and 2007, respectively, and the Ph.D. degree in computer engineering from Stevens Institute of Technology, Hoboken, NJ, in 2011.

Dr. Sheng Chen has published multiple papers on high-profile journals and conferences including IEEE Transactions on Neural Networks and International Conference on Very Large Database. He is serving as a regular peer reviewer for IEEE Transactions on Neural Networks, IEEE Transactions on System, Men, and Cybernetics - Part B, and International Joint Conference on Neural Networks, etc.

His current research interests include computational intelligence, statistical machine learning, and pattern recognition, as well as their applications such as record matching in database and computational linguistics. 

H. He, S. Chen, K. Li, and X. Xu, "Incremental Learning from Stream Data,"  IEEE Trans. Neural Networks, vol. 22, no. 12, pp. 1901-1914, 2011.

S. Chen, A. Borthwick, and V. R. Carvalho, "The Case for Cost-Sensitive and Easy-To-Interpret Models in Industrial Record Linkage," International Conference on Very Large Databases, 2011.

S. Chen and H. He, "Towards Incremental Learning of Nonstationary Imbalanced Data Stream: A Multiple Selectively Recursive Approach,"Evolving Systems, vol. 2, no. 1, pp. 35-50, 2011.

S. Chen, H. He, and E. A. Garcia, “RAMOBoost: Ranked Minority Over-sampling in Boosting,” IEEE Trans. Neural Networks, vol. 21, no. 10, pp. 1624-1642, 2010. 

H. He and S. Chen, “IMORL: Incremental Multiple Objects Recognition and Localization,” IEEE Trans. Neural Networks, vol. 19, no. 10, pp. 1727-178, 2008