贵州大学机械工程学院研究生导师介绍：胡建军

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贵州大学机械工程学院研究生导师胡建军介绍如下：

胡建军，博士生导师,硕士生导师

专业方向：01机械制造及其自动化,02机械电子工程   

电子邮件：hujianju@gmail.com 

研究领域

智能制造与机器人、大数据与数据挖掘、深度学习机器学习与进化计算、材料信息学、生物信息学等。

招生专业

博士研究生专业：机械制造及其自动化，机械电子工程专业

硕士研究生专业：机械制造及其自动化，机械电子工程，机械工程

招生方向

制造自动化与制造物联，智能制造，大数据

工作简历

2016/09-至今，贵州大学，机械工程学院，柔性引进特聘教授、学术带头人
2007/09-至今，美国南卡大学，计算机科学与工程系，终身副教授
2005/07-2007/08，美国南加州大学，计算与分子生物学系，博士后，合作导师：Xianghong Zhou
2004/07-2005/07, 美国普渡大学，计算机科学系，博士后，合作导师: Daisuke Kihara

教育经历

2000/09-2004/07，密西根州立大学，计算机科学与工程系，博士，导师：Erik Goodman
1995/09-1998/03，武汉理工大学，机电工程学院，硕士，导师：张仲甫
1991/09-1995/06，武汉理工大学，机电工程学院，本科

奖励信息

Jianjun Hu, Breakthrough Rising Stars of Research, University of South Carolina, 2010
Jianjun Hu, NSF CAREER Award （美国杰出青年基金）: Computational Analysis and Prediction of Genome-Wide Protein, 美国国家自然科学基金，2009

发表论文

（1） Jonathan Kenneth Bunn, Jianjun Hu*, Jason R. Hattrick-Simpers* (2016) Semi-Supervised Approach to Phase Identification from Combinatorial Sample Diffraction Patterns, JOM, pp doi:10.1007/s11837-016-2033-8. p1-10 2016
（2） Jonathan Kenneth Bunn, Shizhong Han, Yan Tong, Yan Zhang, Jianjun Hu*, and Jason Ryan Hattrick-Simpers*. “Generalized Machine Learning Algorithm for Automatic Phase Attribution in High-throughput Experimental Studies,” Journal of Materials Research, Vol. 30, No. 7, pp. 879– 889, 2015.
（3） J. Hu, Haifeng Li, Michael S Waterman, and Xianghong Jasmine Zhou. “Integrative missing value estimation for micro data”,  BMC Bioinformatics. 7: 449., 2006
（4） J. Hu, Yifeng David Yang and Daisuke Kihara, EMD: an Ensemble Algorithm for discovering regulatory motifs in DNA sequences, BMC Bioinformatics, 7:342. 2006
（5） J. Hu, Bin Li, and Daisuke Kihara, Limitations and Potentials of Current Motif Discovery Algorithms, Nucleic Acid Research, 33: 4899-4913, 2005 (158 citations)
（6） 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
（7） 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.
（8） 胡建军, 汪叔淳, 现代智能制造中的关键智能技术研究综述, 中国机械工程. 第一期，卷7., 1999.
（9） 胡建军，黄安贻，张仲甫，BP网络的权值诱导与层次训练算法，计算机科学，1998（1）62-65.
（10） Zheng Xiong, Yinyan He, Jason Hattric-Simpers, Jianjun Hu* (2017) Automated Phase Segmentation for large-Scale X-ray Diffraction Data using Graph-based Phase Segmentation (GPhase) Algorithm. ACS Combinatorial Sciences. 2017.
（11） J. Hu* and J. Xu, “Density based Pruning for Identification of Differentially Expressed Genes”, BMC Genomics, 11(2):S3, 2010
（12） J. Hu* and Fan Zhang, BayesMotif: De novo Protein Sorting Motif Discovery from Impure Datasets” BMC Bioinformatics, 11(Suppl 1):S66, 2010
（13） Eric Chen, Jianjun Hu* (2016) Computational Identification of Phosphorylation Sites around Nuclear Localization Signal Sequence Reveals New Insight into Genes Associated with Human Diseases. Journal of Bioinformatics and proteomics Review. Rev 3(1):1- 4. 2016
（14） Z. Liu, and J. Hu*, Mislocalization-related disease gene discovery using gene expression based computational protein localization prediction. Methods. v93. p119-127. 2015
（15） J. Lin, Z. Liu, and J. Hu*, Computational identification of post-translational modification (PTM) based nuclear import regulations by characterizing nuclear localization signal-import receptor interaction, Proteins:Structure,Function, and Bioinformatics, ;82(10):2783-96, 2014.
（16） Ananda Mohan Mondal, Jianjun Hu*. Scored Protein-Protein Interaction to Predict Subcellular Localizations for Yeast Using Diffusion Kernel. Lecture Notes in Computer Science,Pattern Recognition and Machine Intelligence Volume 8251, 2013, pp 647-655
（17） J. Lin and J. Hu*, SeqNLS: Nuclear localization signal prediction based on frequent pattern mining and linear motif scoring, PLoS ONE 8(10): e76864. doi:10.1371/journal.pone.0076864, 2013
（18） R. Liu and J. Hu*, DNABind: A hybrid algorithm for structure-based prediction of DNA-binding residues by combining machine learning and template-based approaches. Proteins: Structure, Function, and Bioinformatics, DOI: 10.1002/prot.24330, 2013
（19） J. Lin, A. Mondal, R. Liu and J. Hu*, Minimalist Ensemble Algorithms for Genome-wide Protein Localization Prediction. BMC Bioinformatics, 13:157, 2012
（20） 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
（21） A. Mondal and J. Hu*, “Network Based Prediction of Protein Localization Using Diffusion Kernel”. Int. Journal of Data Mining and Bioinformatics,9(4):386-400, 2014
（22） R. Liu and J. Hu*, “Computational Prediction of Heme-Binding Residues by Exploiting Residue Interaction Network”. PLoS ONE 6(10): e25560., 2011
（23） R. Liu and J. Hu*, “HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information”, BMC Bioinformatics, 2011, 12:207
（24） E. Atilgan and J. Hu*, “Improving Protein Docking Using Sustainable Genetic Algorithms”, International Journal of Computer Information Systems and Industrial Management (IJCISIM), Vol 3, 2011
（25） R. Liu and J. Hu*, “Prediction of discontinuous B-cell epitopes using logistic regression and structural information”, Journal of Proteomics & Bioinformatics, 4: 010-015, 2011
（26） E. Atilgan and J. Hu*, “Improving Protein Docking Using Sustainable Genetic Algorithms”, International Journal of Computer Information Systems and Industrial Management (IJCISIM), Vol 3, 2011
（27） S. Li, X. Chen and J. Hu*. 基于层次搜索的可持续性进化算法研究，中国机械工程, 7(11), 2006.
（28） 郭燕利,吴立意,胡建军*,张仲甫,平面二次包络环面蜗轮副研究综述与展望.机械制造 . 2001 (04)
(29)Shaoboli, Zheng Xiong, Jianjun Hu*, Inferring Phase Diagrams from X-ray Diffraction data with large background signals using Graph Segmentation Algorithm (BGPhase),Materials Science and Technology, Pages 315-326. 2017. https://doi.org/10.1080/02670836.2017.1389116
[Journal Impact Factor:1.538]
(30)Li, S.; Chen, W.; Hu, J.; Hu, J.*， ASPIE: A Framework for Active Sensing and Processing of Complex Events in the Internet of Manufacturing Things. Sustainability 2018, 10, 692.
[Journal Impact Factor:1.789]
(31)Li, S.; Wu, Y.; Xu, Y.; Hu, J.; Hu*, J. A Bayesian Network Based Adaptability Design of Product Structures for Function Evolution, Applied. Science. 2018, 8, 493.
[Journal Impact Factor:1.67]
(32)Shaobo Li , Wang Zou , Jianjun Hu *,Novel Evolutionary Algorithm for Designing Robust Analog Filters, Algorithms 2018, 11(3), 26; doi:10.3390/a11030026
[EI indexed]
(33)Jie Hu, Shaobo Li*, Guanci Yang, Jianjun Hu, A Hierarchical Feature Extraction Model for Multi-label Mechanical Patent Classification, Sustainability 2018, 10(1), 219; doi:10.3390/su10010219.
[Journal Impact Factor:1.78]
(34)Shaohua Luo, Shaobo Li, Farid Tajaddodianfar, Jianjun Hu*, Observer-based adaptive stabilization of the fractional-order chaotic MEMS resonators, Nonlinear Dynamics, 2018, DOI:10.1007/s11071-018-4109-1
[Journal Impact Factor:3.46]
(35)Jie Hu, Shaobo Li, Yong Yao, Liya Yu, Guanci Yang, Jianjun Hu*, Patent Keywords Extraction Algorithm based on Distributed Representation for Patent Classification. Entropy 2018, 20(2), 104; doi:10.3390/e20020104
[Journal Impact Factor:1.82]
(36)Shaohua Luo, Shaobo Li, Farid Tajaddodianfar, Jianjun Hu*, Adaptive synchronization of fractional-order arch micro- electro-mechanical system, IEEE Sensors,18(9), pp3524-3532, 2018
[Journal Impact Factor:2.52]

(37)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.
[Journal Impact Factor:2.67]
(38)Emrah Atilgan, Jianjun Hu， First-Principle based Computational Doping of SrTiO3 Using Combinatorial Genetic Algorithms, Bulletin of Materials Science. February 2018, 41:1
(39)Jianjun Hu, Zhonghao Liu, DeepMHC: Deep Convolutional Neural Networks for High-performance peptide-MHC Binding Affinity Prediction, bioRxiv 239236; doi:  https://doi.org/10.1101/239236.
(40)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.
(41)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
(42)Xuemei Chen,Chenglong Zhang, Shaobo Li, Jianjun Hu, Improving Rolling Bearing Fault Diagnosis by DS Evidence Theory Based Fusion Model, Journal of Sensors,  2017(1):1-14 • October

发表著作

遗传编程与机电系统创新设计，机械工业出版社，2009
（1） J. Hu, Zhun Fan, Jiachuan Wang, Shaobo Li, Kisung Seo, Xiangdong Peng, Janis Terpenny, Ronald Rosenberg, and Erik Goodman, “GPBG: A Framework for Evolutionary Design of Multi-domain Engineering Systems Using Genetic Programming and Bond Graphs”. In Evolution by Design – Advances in Evolutionary Design. P. F. Hingston et. al. (ed.) Springer publisher, 2008.
（2） J. Hu, S. Li & E. Goodman. “Evolutionary Robust Design of Analog Filters using Genetic Programming,” in Evolutionary Computation in Dynamic and Uncertain Environments,  Kacprzyk, J. (ed.), Springer, pp. 479-496, 2007
（3） J. Hu, E. Goodman, “Domain Specificity of Genetic Programming based Automated Synthesis: a Case Study with Synthesis of Mechanical Vibration Absorbers”, in Genetic Programming Theory and Practice. Rick Riolo and Bill Worzel (eds.). Kluwer Publishers, Boston, MA. 2005.
（4） J. Hu, E. Goodman, “Evolving robust dynamic systems with genetic programming”. In Genetic Programming Theory and Practice. Rick Riolo and Bill Worzel (eds.). Kluwer Publishers, Boston, MA. 2004.
（5） J. Hu, K. Seo, E. Goodman, R. Rosenberg, “Toward efficient topological synthesis of dynamic systems using bond graphs and genetic programming”. Nadia Nedjah. (eds). Evolutionary Machine Design: Methodology and Applications. Nova Science Publishers, NY, USA, 2004.
（6） J. Hu, E. Goodman and K. Seo, “Continuous Hierarchical Fair Competition Model for Sustainable Innovation in Genetic programming”. In Genetic Programming Theory and Practice. Rick Riolo and Bill Worzel (eds.). Kluwer Publishers, Boston, MA. 2003.

科研项目

1. 美国 South Carolina Department of Transportation, research project Big data analytics of SCDOT equipment and vehicles Phase-II, 2016/3-2016/8
2．University of South Carolina, Building a disaster-resilient community: A study of community social support during the 2015 flooding, USC, 11/01/2015 - 05/31/2016
3. 美国 South Carolina Department of Transportation， research project， Big data analytics of SCDOT equipment and vehicles,2015/3-2015/8
4. 美国自然科学基金委, NSF CAREER Award （美国杰出青年基金）, Computational Analysis and Prediction of Genome-Wide Protein Targeting Signals and Localization, 2009/09-2015/08
5. 美国Elsa U. Pardee Foundation, Identification of novel biomarkers for breast cancer stem cells,2009/09-2010/10

6.Big data analytics of HIV treatment gaps in south carolina: identification and prediction, 美国国家卫生研究所NIH, $3,101,969,07/01/2017-06/30/2022, with Xiaoming Li(PI).
7. RII Track 1: Materials Assembly and Design Excellence in South Carolina: MADE in SC (MADEinSC), 美国自然科学基金委 National Science Foundation, $20 million, September 1, 2017 - August 31, 2022, with Rakash Nagarkatti (PI)

7.国家自然科学基金应急项目《基于机器学习与图像处理算法的高通量组合材料实验相图生成与物相辨识方法研究》，2018.01 2018 02