貴州大學機械工程學院研究生導師介紹：胡建軍

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貴州大學機械工程學院研究生導師胡建軍介紹如下：

胡建軍，博士生導師,碩士生導師

專業方向：01機械制造及其自動化,02機械電子工程   

電子郵件：hujianju@gmail.com 

研究領域

智能制造與機器人、大數據與數據挖掘、深度學習機器學習與進化計算、材料信息學、生物信息學等。

招生專業

博士研究生專業：機械制造及其自動化，機械電子工程專業

碩士研究生專業：機械制造及其自動化，機械電子工程，機械工程

招生方向

制造自動化與制造物聯，智能制造，大數據

工作簡歷

2016/09-至今，貴州大學，機械工程學院，柔性引進特聘教授、學術帶頭人
2007/09-至今，美國南卡大學，計算機科學與工程系，終身副教授
2005/07-2007/08，美國南加州大學，計算與分子生物學系，博士后，合作導師：Xianghong Zhou
2004/07-2005/07, 美國普渡大學，計算機科學系，博士后，合作導師: Daisuke Kihara

教育經歷

2000/09-2004/07，密西根州立大學，計算機科學與工程系，博士，導師：Erik Goodman
1995/09-1998/03，武漢理工大學，機電工程學院，碩士，導師：張仲甫
1991/09-1995/06，武漢理工大學，機電工程學院，本科

獎勵信息

Jianjun Hu, Breakthrough Rising Stars of Research, University of South Carolina, 2010
Jianjun Hu, NSF CAREER Award （美國杰出青年基金）: Computational Analysis and Prediction of Genome-Wide Protein, 美國國家自然科學基金，2009

發表論文

（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） 胡建軍, 汪叔淳, 現代智能制造中的關鍵智能技術研究綜述, 中國機械工程. 第一期，卷7., 1999.
（9） 胡建軍，黃安貽，張仲甫，BP網絡的權值誘導與層次訓練算法，計算機科學，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*. 基于層次搜索的可持續性進化算法研究，中國機械工程, 7(11), 2006.
（28） 郭燕利,吳立意,胡建軍*,張仲甫,平面二次包絡環面蝸輪副研究綜述與展望.機械制造 . 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

發表著作

遺傳編程與機電系統創新設計，機械工業出版社，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.

科研項目

1. 美國 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. 美國 South Carolina Department of Transportation， research project， Big data analytics of SCDOT equipment and vehicles,2015/3-2015/8
4. 美國自然科學基金委, NSF CAREER Award （美國杰出青年基金）, Computational Analysis and Prediction of Genome-Wide Protein Targeting Signals and Localization, 2009/09-2015/08
5. 美國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, 美國國家衛生研究所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), 美國自然科學基金委 National Science Foundation, $20 million, September 1, 2017 - August 31, 2022, with Rakash Nagarkatti (PI)

7.國家自然科學基金應急項目《基于機器學習與圖像處理算法的高通量組合材料實驗相圖生成與物相辨識方法研究》，2018.01 2018 02