Personal Information
  • Associate professor
  • Supervisor of Master's Candidates
  • Name (Simplified Chinese):shi mingguang
  • Name (English):shi mingguang
  • Name (Pinyin):shi mingguang
  • School/Department:电工与电子技术系
  • Education Level:With Certificate of Graduation for Doctorate Study
  • Business Address:逸夫楼11楼
  • Gender:Male
  • Degree:Doctoral degree
  • Status:Employed
  • Alma Mater:中国科学技术大学
  • Discipline:Control Theory and Engineering
    Pattern Recognition and Intelligent Systems
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史明光:男,副教授,博士,硕士生导师。学习经历1996年7月于合肥工业大学获工业电气自动化学士学位,2004年4月于合肥工业大学获控制理论与应用硕士学位,2009年6月于中国科学技术大学获模式识别与智能系统专业博士学位,2010年1月至2012年3月美国范德比尔特大学(Vanderbilt University)博士后, Postdoc research fellow。研究方向研究领域为人工智能, 主要包括机器学习、模式识别与生物信息学。主持项目1) 国家自然科学基金面上基金,基于随机游走图和样本几何与标记信息的混合模型构造直推SVM的癌症转移复发分类。2) 国家自然科学基金面上基金,基于多组学数据融合与谱聚类随机行走模型挖掘二维致癌抑癌基因群失调网络算法研究。3) 安徽省自然科学基金面上基金,结直肠癌复发转移分子标志物的网络化挖掘算法研究。4) 合肥工业大学博士专项资金,蛋白质相互作用关系预测的核方法研究。5) 电力设备图像检测的深度学习模型发表论文与发明专利做为通讯作者与第一作者发表SCI论文多篇,其中JCR一区与二区论文多篇, 2篇中科院一区TOP期刊 (Briefings in Bioinformatics, 2021,2023),9篇影响因子大于3.0。授权国家发明专利4项。 1) Shi, M., Li, X., Li, M., Si, Y. Attention-based generative adversarial networks improve prognostic outcome prediction of cancer from multimodal data. Briefings in Bioinformatics, 2023, 24(6): bbad329. (通讯作者)2) Tang, Y. Li, X. and Shi, M. LIDER: cell embedding based deep neural network classifier for supervised cell type identification, PeerJ, 2023, 11:e15862. (通讯作者)3) Shi, M., Sheng,Z. and Tang, H. Prognostic outcome prediction by semi-supervised least squares classification. Briefings in Bioinformatics, 2021,22(4):1-9. (通讯作者)4) Shi, M., Wang J and Zhang C. Integration of Cancer Genomics Data for Tree‐based Dimensionality Reduction and Cancer Outcome Prediction. Molecular Informatics, 2020, 39(3):1-12. (通讯作者)5) Shi, M. and Xu G . Development and validation of GMI signature based random survival forest prognosis model to predict clinical outcome in acute myeloid leukemia. BMC Medical Genomics, 2019, 12(1):90-105. (通讯作者)6) Shi, M. and Xu, G. Spectral clustering using Nyström approximation for the accurate identification of cancer molecular subtypes, Scientific Reports, 2017; 7, 4896.(通讯作者)7) Shi, M. and He, J. ColoFinder: a prognostic 9-gene signature improves prognosis for 871 stage II and III colorectal cancer patients, Peerj, 2016; 4, e1804. (通讯作者)8) Shi, M. and He, J. SNRFCB: sub-network based random forest classifier for predicting chemotherapy benefit on survival for cancer treatment, Molecular Biosystems, 2016; 12, 1214-1223. (通讯作者)9) Shi M, Wu M, Pan P, Zhao R. Network-based sub-network signatures unveil the potential for acute myeloid leukemia therapy. Molecular bioSystems 2014. (通讯作者)10) He J, Hu M, Shi M, Liu Y. Research on the measure method of complaint theme influence on online social network. Expert Systems with Applications 2014;41:6039-46.11) Shi M, Beauchamp RD, Zhang B. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients. PloS one 2012;7:e41292.12) Shi M, Zhang B. Semi-supervised learning improves gene expression-based prediction of cancer recurrence. Bioinformatics 2011;27:3017-23.13) Shi M-G, Xia J-F, Li X-L, Huang D-S. Predicting protein–protein interactions from sequence using correlation coefficient and high-quality interaction dataset. Amino Acids 2010;38:891-99.14) Shi M-G, Wu M, Huang D-S, Li X-L: Inferring protein interactions from sequence using support vector machine Neural Networks, 2009. IJCNN 2009. International Joint Conference on 2009:2903-07.15) Shi M-G, Huang D-S, Li X-L. A protein interaction network analysis for yeast integral membrane protein. Protein and peptide letters 2008;15:692-99.16) 史明光, 陈无畏. 基于博弈论的 H2/H∞ 混合控制及其在汽车主动悬架中的应用. 控制理论与应用 2006;22:882-88. 社会兼职国家自然科学基金通讯评审专家(2016-)教育部学位中心抽检学位论文通讯评议专家(2021-)安徽省科技厅科技项目评审专家(2022-)国际期刊Plos One academic editor(2024-) 研究生培养招生方向:控制科学与工程;电子信息指导研究生两人获得国家奖学金,多人获得校三好学生。 通信地址:安徽省合肥市屯溪路193号合肥工业大学电气与自动化学院邮政编码:230009邮箱: mingguang.shi@hfut.edu.cnQQ:1306778731

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Doctoral degree

shi mingguang
Hefei University of Technology
MOBILE Version