Jianjun Hu CV

Associate Professor

Department of Computer Science and Engineering
University of South Carolina
Columbia, SC 29208
Office: 2223 Storey Innovation Center
Phone: 803-777-7304  
   Fax: 803-777-3767
 Email: jianjunh_AT_cse.sc.edu

Office hours:TBD



I am looking for highly motivated Ph.D. students with RA assistantship to join my lab and work on projects in Deep Learning, material informatics, bioinformatics,data mining or machine learning. You are expected to have good programming skills and teamwork spirit.

Teaching

Spring 2018

Mobile Application Development (CSCE546)
TTH 1:15PM- 2:30PM, 301 Main St. B110
Scientific Application Programming (CSCE206)
TTH 10:05PM- 11:30PM, SWGN 2A14

Research Interests

My research interests are in the areas of machine learning, deep learning, data mining, big data, evolutionary computation and their applications in bioinformatics, material informatics, and health informatics. Our research has been sponsored by NSF, NIH, Nvidia, and the South Carolina Department of Transportation. Currently, our major research focus is developing deep learning algotrithms for solving challenging application problems such as: 

  • Intelligent audio/sound processing
  • Data-driven material discovery
  • Disease diagnosis and prediction, medical image analysis
  • Bioinformatics: protein-peptide binding prediction for drug design, and protein design
  • Big data driven predictive analytics for healthcare
  • Fault diagnosis, text mining, and intelligent transportation

 

For more information, pls visit my lab's homepage here: Machine Learning and Evolution Group (MLEG)

Bio: I joined CSE department of the University of South Carolina in August 2007. I am now working on deep learning, data mining and their applications in audio processing, material informatics, bioinformatics, and health informatics.  I got my Ph.D. in Computer Science in the area of machine learning and particularly evolutionary computation at the Genetic Algorithm Research and Application Group (GARAGe) of Michigan State University. My dissertation focuses on sustainable evolutionary computation algorithms and automated computational synthesis. I have worked as Postdoc at  Purdue University Computational Molecular Biology Division at the University of Southern California.

Education

Postdoc University of Southern California, Computational Molecular Biology 09/05 - 06/07
Postdoc Purdue University, Biological Science 09/04 - 08/05
Ph.D.  Michigan State University, Computer Science 08/00 - 07/04
M.S.  Wuhan University of Technology, China, Mechanical Engineering 07/95 - 04/98
B.S.  Wuhan University of Technology, China, Mechanical Engineering 09/91 - 07/95

Selected Publications [Complete List]

Dissertation

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. Advisor: Erik Goodman
   

Selected Journal Publications

1 Jianjun Hu, Zhonghao Liu, DeepMHC: Deep Convolutional Neural Networks for High-performance peptide-MHC Binding Affinity Prediction, bioRxiv 239236; 2017 doi: https://doi.org/10.1101/239236. Click to download PDF File
2 S Li, G Liu, X Tang, J Lu, J Hu, An Ensemble Deep Convolutional Neural Network Model with Improved DS Evidence Fusion for Bearing Fault Diagnosis, Sensors 2017, 17(8), 1729; doi:10.3390/s17081729.
3 Zheng Xiong, Yinyan He, Jason Hattric-Simpers, Jianjun Hu (2017) Automated Phase Segmentation for large-Scale X-ray Diffration Data using Graph-based Phase Segmentation (GPhase) Algorithm, ACS Combinatorial Sciences. DOI: 10.1021/acscombsci.6b00121
4 H. Luo, R. Benner, R. A. Long, J. Hu, "Subcellular Localization of Marine Bacterial Alkaline Phosphatases " Proceeding of National Academy of Science (PNAS), November 19, 2009 Click to download PDF File
5 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 , Special Issue on Genetic programming for human-competitive design
6 Shaoboli, Zheng Xiong, Jianjun Hu (2017) Inferring Phase Diagrams from X-ray Diffraction data with large background signals using Graph Segmentation Algorithm (BGPhase), Materials Science and Technology, (accepted). 2017
7 J. Hu, Yifeng David Yang and Daisuke Kihara, "EMD: an Ensemble Algorithm for discovering regulatory motifs in DNA sequences", BMC Bioinformatics, 7:342. 2006. Click to download PDF File
8 J. Hu, Bin Li, and Daisuke Kihara, "Limitations and Potentials of Current Motif Discovery Algorithms", Nucleic Acid Research, 33: 4899-4913, 2005Click to download PDF File
9 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 , Special Issue on Genetic programming for human-competitive design Click to download PDF File
10 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. Click to download PDF File

Conference Publications

1 A. Mondal and J. Hu, "Protein Localization by Integrating Multiple Protein Correlation Networks", Proceeding of 2012 International Conference on Bioinformatics and Computational Biology (BIOCOMP12), 2012
2 A. Mondal and J. Hu, "NetLoc: Network Based Protein Localization Prediction Using Protein-Protein Interaction and Co-expression Networks", Proceeding of IEEE International Conference on Bioinformatics & Biomedicine (BIBM2010)
3 F. Zhang and J. Hu, "Bayesian Classifier for Anchored Protein Sorting Discovery", Proceeding of 2009 IEEE International Conference on Bioinformatics & Biomedicine (BIBM09: Nov1-4 2009, USA).
4 J. Hu and F. Zhang (2009), Improving Protein Localization Prediction Using Amino Acid Group Based Physichemical Encoding”. Lecture Notes in Computer Science. Bioinformatics and Computational Biology BiCoB2009. 5462/2009. Springer Berlin / Heidelberg
5 J. Hu, X. Zhong, E. Goodman, “Open-ended Robust Design of Analog filters Using Genetic Programming”, Proc. Genetic and Evolutionary Computation Conference. (Best paper nominee), 2005
6 J. Hu, E. Goodman, “Robust and Efficient Genetic Algorithms with Hierarchical Niching and Sustainable Evolutionary Computation Model”, Proc.Genetic and Evolutionary Computation Conference.2004
7 J. Hu, E. Goodman, “Wireless Access Point Configuration by Genetic Programming”, Proc. IEEE Congress on Evolutionary Computation (CEC) 2004.
8 J. Hu, E. Goodman, and R. Rosenberg, “Topological search in automated mechatronic system synthesis using bond graphs and genetic programming”, Proc. of American Control Conference (ACC), 2004.
9 J. Hu, K. Seo, Z. Fan, R. Rosenberg, and E. Goodman, " HEMO: A Sustainable Multi-Objective Evolutionary Optimization Framework", Proc. 2003 Genetic and Evolutionary Computation Conference, Chicago, Springer, Lecture Notes in Computer Science, July, pp. 1029-1040, 2003