1992.09–1996.07，伟德国际1949官方网站，物理系，国家基础理论人才培养基地，学士
　　1996.09–1999.07，伟德国际1949官方网站，物理系，凝聚态物理专业，硕士
　　2002.08–2004.07，美国新墨西哥州立大学，计算机科学系，硕士
　　2004.09–2007.12，美国新墨西哥州立大学，计算机科学系，博士

　　2007.12–2010.02，美国休斯敦壳牌石油公司Savior 软件部，软件工程师
　　2010.03–2015.05，伟德国际1949官方网站伟德betvlctor体育官网，副教授
　　2015.06-至今,伟德国际1949官方网站伟德betvlctor体育官网，教授

　　主讲本科生课程：《算法设计与分析》
　　主讲研究生课程：《数理统计与随机过程》、《链路挖掘》

　　2010年开始指导硕士研究生（已毕业25人，13人在读）
　　2017年开始指导博士研究生（在读5人）

　　机器学习、模式识别、计算机视觉、生物信息

　　硕士（计算机软件与理论、计算机技术、软件工程），博士（计算机应用）

主持参与完成的项目：

国家自然科学基金面上项目(项目编号：61272213)

中央高校基本科研业务费重要学科领域项目(项目代码：lzujbky-2011-k33)

中国石油勘探开发研究院西北分院技术开发项目(项目编号：(12)0536)

中国科学院近代物理研究所技术开发项目(项目编号：(12)0208)

 

目前在研项目：

国家重点研发计划子课题(项目编号：2017YFE0111900，主持)

国家重点研发计划子课题(项目编号：2018YFB1003205，参与)

发表SCI/EI论文50余篇，近5年主要的SCI/EI论文如下：

[1]Huanqian Yan, Lei Wang, Yonggang Lu*, (2019). “Identifying cluster centroids from decision graph automatically using a statistical outlier detection method”, Neurocomputing, 329, 348-358. DOI: 10.1016/j.neucom.2018.10.067

[2]Xu Han, Li Li and Yonggang Lu*, (2019). “Selecting Near-Native Protein Structures from Predicted Decoy Sets Using Ordered Graphlet Degree Similarity”, Genes, 10(2), 132-144;DOI: 10.3390/genes10020132

[3]Xin Hong, Hailin Li, Paul Miller, Jianjiang Zhou, Ling Li, Danny Crookes, Yonggang Lu, Xuelong Li, Huiyu Zhou, (2019). “Component-based Feature Saliency for Clustering”, IEEE Transactions on Knowledge and Data Engineering. DOI: 10.1109/TKDE.2019.2936847

[4]Xiangwen Wang, Yonggang Lu*, Zhenyu Lu, Xingcheng Ran, Jiaxuan Liu, (2019). A Weighted Voting Algorithm for Detecting Reliable Common Lines in Single Particle Cryo-EM, BIBM 2019:98-101. DOI: 10.1109/BIBM47256.2019.8983199

[5]Xingcheng Ran, Yonggang Lu*, Xiangwen Wang, and Zhenyu Lu, (2019). Hypergraph clustering by generating large pure hyperedges using greedy neighborhood search, FSDM 2019: 152-159.DOI:10.3233/FAIA190176

[6]Wenjie Guo, Li Yang, Yonggang Lu*, Yi Yang, Lian Li, Zongli Liu, (2019).Information Hiding in OOXML Format Data based on the Splitting of Text Elements. ISI 2019: 188-190. DOI: 10.1109/ISI.2019.8823564

[7]Peiyu Kang, Yonggang Lu*, Diqi Pan, Wenjie Guo. (2019). Improving the Dictionary Construction in Sparse Representation using PCANet for Face Recognition. ICPRAM 2019: 517-523. DOI: 10.5220/0007368105170523

[8]Diqi Pan, Yonggang Lu*, Peiyu Kang. (2019). A Deep Learning Model for Multi-label Classification Using Capsule Networks. ICIC 2019: 144-155.DOI: 10.1007/978-3-030-26763-6_14

[9]Li Li, Huanqian Yan, Yonggang Lu*, (2018). “Selecting Near-native Protein Structures from Ab Initio Models Using Ensemble Clustering”, Quantitative Biology, 6, 307–312. DOI: 10.1007/s40484-018-0158-1.

[10]Zhiqiang Zhang, Yonggang Lu, Shaoliang Peng, A Dictionary Learning Algorithm for Gene Expression Profile Classification Based on Feature Selection, IRCE 2018: 203-207.DOI: 10.1109/IRCE.2018.8492929

[11]Lei Wang, Yonggang Lu*, Huanqian Yan, (2018). “A Fast and Robust Grid-Based Clustering Method for Dataset with Arbitrary Shapes”, FSDM 2018: 636-645. DOI: 10.3233/978-1-61499-927-0-636.

[12]Qi Wang, Yonggang Lu*, (2018). “Relationship Between Weight Correlation of the Convolution Kernels and the Optimal Architecture of CNN”, FSDM 2018: 653-662. DOI: 10.3233/978-1-61499-927-0-653

[13]Jing He, Kamal Al-Nasr, Weitao Sun, Yonggang Lu, (2018). “Special Issue Preface: The 9th Computational Structural Bioinformatics Workshop”. Journal of Computational Biology 25(1): 1-2 (2018). DOI: 10.1089/cmb.2018.29010.jh.

[14]Xiangyu Jiang, Yonggang Lu*, Zhenyu Lu, Huiyu Zhou, (2018). “Smartphone-Based Human Activity Recognition Using CNN in Frequency Domain”. APWeb/WAIM 2018: 101-110. DOI: 10.1007/978-3-030-01298-4_10.

[15]Zhijuan Wang, Yonggang Lu*, (2018). “Improving Initial Model Construction in Single Particle Cryo-EM by Filtering Out Low Quality Projection Images”. ICIC: 589-600. DOI: 10.1007/978-3-319-95933-7_68.

[16]Huanqian Yan, Yonggang Lu*, and Heng Ma, (2018). “Density-based Clustering using Automatic Density Peak Detection”, ICPRAM 2018. ICPRAM 2018: 95-102. DOI: 10.5220/0006572300950102.

[17]Yonggang Lu, Ye Wei, Li Liu, Jun Zhong, Letian Sun, Ye Liu. (2017). “Towards unsupervised physical activity recognition using smartphone accelerometers”. Multimedia Tools and Applications, 76:10701-10719.DOI: 10.1007/s11042-015-3188-y.

[18]Huanqian Yan, Yonggang Lu* and Li Li, (2017). “A Potential-based Density Estimation Method for Clustering using Decision Graph”, IDEAL 2017: 73-82. DOI: 10.1007/978-3-319-68935-7_9.

[19]Xianlong Wang, Yonggang Lu*, Dachuan Wang, Li Liu, and Huiyu Zhou, (2017). “Using Jaccard Distance Measure for Unsupervised Activity Recognition with Smartphone Accelerometers”, APWeb-WAIM 2017: 74-83. DOI: 10.1007/978-3-319-69781-9_8.

[20]Tian Wang, Yonggang Lu*, Yuxuan Han. (2017). “Clustering of High Dimensional Handwritten Data by an Improved Hypergraph Partition Method”, ICIC 2017: 323-334. DOI: 10.1007/978-3-319-63315-2_28.

[21]Yonggang Lu, Jiangang Qiao, Xiaochun Wang. (2017). “K-normal: An Improved K-means for Dealing with Clusters of Different Sizes”. ICIC 2017: 335-344. DOI: 10.1007/978-3-319-63315-2_29.

[22]Hu Cao, Yonggang Lu*, (2017). “Using Variable-length Aligned Fragment Pairs and an Improved Transition Function for Flexible Protein Structure Alignment.” Journal of Computational Biology. Vol. 24(1), pp. 2-12. Jan., 2017. DOI:10.1089/cmb.2016.0135

[23]张变兰，路永钢*，张海涛，(2017). “基于KL散度和近邻点间距离的球面嵌入算法”，《计算机应用》，37(3): 680-683, 690.

[24]Yonggang Lu*, Xiaoli Hou, Xurong Chen. (2016). “A Novel Travel-Time Based Similarity Measure for Hierarchical Clustering.” Neurocomputing. Vol. 173, pp. 3-8. DOI: 10.1016/j.neucom.2015.01.090.

[25]Xingmei Liu, Yonggang Lu*, Hu Cao, (2016). “Non-sequential Protein Structure Alignment Based on Variable Length AFPs Using the Maximal Clique.” BIBM 2016:1720-1725. DOI: 10.1109/BIBM.2016.7822777.

[26]Jinyang Yan, Yonggang Lu*, Jing He, (2016). “Selecting Near-native Structures From Decoys Using Maximal Cliques.” BIBM 2016: 1745-1748. DOI: 10.1109/BIBM.2016.7822781.

[27]Haitao Zhang, Zhuo Cheng, Cong Tian, Yonggang Lu, Guoqiang Li, (2016). “Verifying OSEK/VDX applications: An optimized SMT-based bounded model checking approach.” ICIS 2016: 1-6. DOI: 10.1109/ICIS.2016.7550826.

[28]Heng Ma, Yonggang Lu* and Haitao Zhang, (2016). “Determining the Near Optimal Architecture of Autoencoder using Correlation Analysis of the Network Weights”, IJCCI 2016:53-61. DOI: 10.5220/0006039000530061.

[29]Dachuan Wang, Li Liu, Xianlong Wang, Yonggang Lu*, (2016). 'A Novel Feature Extraction Method on Activity Recognition Using Smartphone.' Lecture Notes in Computer Science,Volume 9998, pp. 67-76.

[30]Xili Sun, Yonggang Lu*. (2016). “Locally linear embedding based on Rank-order distance.” ICPRAM 2016: 162-169. DOI: 10.5220/0005658601620169

[31]田守财，孙喜利，路永钢*，(2016)，“基于最近邻的随机非线性降维”,《计算机应用》,36卷，2期，377-381页.

[32]Xili Sun, Shoucai Tian, Yonggang Lu*. (2015). “High Dimensional Data Clustering by Partitioning the Hypergraphs using Dense Subgraph Partition”, Proceedings of SPIE, 98130B. pp. 98130B-1 - 98130B-9, DOI: 10.1117/12.2205743

[33]Ye Wei, Li Liu, Jun Zhong, Yonggang Lu*, and Letian Sun，(2015).“Unsupervised Race walking recognition using smartphone accelerometers”, Lecture Notes in Computer Science, Vol. 9403, pp 691-702. DOI:10.1007/978-3-319-25159-2_63

[34]Hu Cao, Yonggang Lu*, (2015). “Flexible Protein Structure Alignment by Variable-length Aligned Fragment Pairs.” BIBM 2015:1280-1286. DOI: 10.1109/BIBM.2015.7359864.

我们组与以下国外研究机构的研究者有着长期合作：

美国拉斯阿拉莫斯国家实验室(Los Alamos National Lab)

美国新墨西哥州立大学(New Mexico State University)

美国德雷塞耳大学(Drexel University)

美国欧道明大学(Old Dominion University)

英国莱斯特大学(University of Leicester)

ICPRAM 2018国际会议最佳论文奖

担任 中国计算机学会生物信息学专业组委员

担任 中国人工智能学会科普工作委员会委员

担任 国家自然科学基金重点项目、面上项目和青年项目学术评委

担任 国家科学技术奖评审专家

担任BIBM国际会议程序委员会委员

担任《软件》杂志第十二届期刊编委

担任《计算机学报》期刊学术评委

担任《自动化学报》期刊学术评委

担任《Neurocomputing》期刊学术评委

担任《IEEE Trans. on Neural Networks and Learning Systems》期刊学术评委

担任《IEEE Trans. On Systems, Man, and Cybernetics》期刊学术评委

担任《IEEE & ACM Transactions on Computational Biology and Bioinformatics》期刊学术评委

担任《IEEE Access》期刊学术评委

担任《Journal of Computational Biology》期刊学术评委

担任《International Journal of Data Mining and Bioinformatics》期刊学术评委

担任《International Journal of Pattern Recognition and Artificial Intelligence》期刊学术评委

担任《Computers and Electrical Engineering》期刊学术评委

担任《Briefings in Functional Genomics》期刊学术评委

担任 伟德国际1949官方网站伟德betvlctor体育官网 学术委员会委员