Hu

Professor Hu's research interests are in the area of bioinformatics, machine learning, evolutionary computation, and data mining. The rapid accumulation of large-scale high-throughput biological data such as genome sequences, microarray gene expression, and protein-protein interactions are creating a great opportunity for biological knowledge discovery and mining. His major research focus is to integrate heterogeneous data and algorithms to understand signals, logic, and models in gene regulatory networks, protein localization, and virtual screening. He is also interested in hybrid machine learning and evolutionary algorithms as well as automated evolutionary design. Ongoing research efforts include decoding the protein "zip code", the signals during protein subcellular localization, microarray analysis, and virtual screening.

Education

• Postdoc., University of Southern California (2005-2007)
• Postdoc., Purdue University (2004-2005)
• Ph. D., Michigan State University (2004)
• B. S., Wuhan University of Technology (1995)

Selected Publications

• J. Hu, E. D. Goodman, and R. C. Rosenberg. Automated Synthesis of Mechanical Vibration Absorbers Using Genetic Programming. Journal of Artificial Intelligence for Engineering Design, Analysis and Manufacturing. 22(3), 2008.
• J. Hu, Haifeng Li, Michael S Waterman, and Xianghong Jasmine Zhou. Integrative missing value estimation for microarray data. BMC Bioinformatics. 7: 449., 2006.
• J. Hu, Yifeng David Yang and Daisuke Kihara, "EMD: an Ensemble Algorithm for discovering regulatory motifs in DNA sequences", BMC Bioinformatics, 7:342. 2006.
• J. Hu, Bin Li, and Daisuke Kihara, "Limitations and Potentials of Current Motif Discovery Algorithms", Nucleic Acid Research, 33: 4899-4913, 2005.
• J. Hu, E. Goodman, K.Seo, Z. Fan, R. Rosenberg, "The Hierarchical Fair Competition (HFC) Framework for Sustainable Evolutionary Algorithms", Evolutionary Computation, 13 (2), MIT Press, 2005.
• J. Hu. Sustainable Evolutionary Algorithms and Scalable Evolutionary Synthesis of Dynamic Systems. PhD thesis, Department of Computer Science and Engineering, Michigan State University, East Lansing, Michigan, 48823, USA, 2004.