高敬阳,博士,教授

发布人:信息学院发布时间:2020-03-31浏览次数:2605

    高敬阳,博士,教授,博士生导师,计算机系主任。北京市教学名师、霍英东教育基金会第8届青年教师奖。主要研究领域包括人工智能、基于深度学习的医学影像分析、基于机器学习和深度学习的基因组学大数据分析、模式识别理论与应用等。

    担任中国计算机学会高级会员、中国人工智能学会高级会员、中国计算机学会人工智能与模式识别专委会委员、中国计算机学会生物信息学专委会首批委员等。主编出版教材3部。

邮箱:gaojy@mail.buct.edu.cn



教学课程 Teaching Courses

课程名称课程备注
程序设计基础本科生
计算机科学导论本科生
大学计算机(中国大学MOOC平台课程)本科生
C语言程序设计(中国大学MOOC平台课程)本科生


主要科研项目 Research Projects

项目名称项目来源
基于多检测理论融合的基因组结构变异综合检测方法国家自然科学基金面上项目
基因组缺失变异特征增强表达及精准检测北京市自然科学基金面上项目
基于深度学习及二代测序数据的肺癌驱动基因精准检测北化-中日联合基金项目


主要成果、奖励 Main Achievements and Awards

  1. 北京市教学名师

  2. 霍英东教育基金会第8届青年教师奖


学术论文 Research Publications

    ● Cai L, Wu YF, Gao JY*. DeepSV: accurate calling of genomic deletions from high-throughput sequencing data using deep convolutional neural network. BMC BIOINFORMATICS, DEC 12 2019. 20(1),p665

    ● Wu Zhongjia,Wu Yufeng, Gao Jingyang*. InvBFM:finding genomic inversions from high-throughput sequence data based on feature mining. BMC GENOMICS. MAR 5 2020,21(1):p173

    ● Bai Ruofei, Gao Liwei, Ling Cheng, Gao Jingyang*. CnnSV-Typer: Calling of structural variation genotype based on CUDA acceleration. 21st IEEE International Conference on High Performance Computing and Communications, HPCC 2019, August 10-12, 2019.

    ● Xiaodong Zhang, Jingyang Gao*. Concod: Accurate Consensus-based Approach of Calling Deletions from High-throughput Sequencing Data. The 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Shenzhen,China,Dec 15-18,2016.(CCF  B类)

    ● Lei Cai, Jingyang Gao*. Concod: an effective integration framework of consensus-based calling deletions from next-generation sequencing data. International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 17, No. 2, 2017,pp153-172.

    ● Jing Wang, Jingyang Gao*. Deletion genotype calling on the basis of sequence visualization and image classification. Int. J. Data Mining and Bioinformatics.2018, 20(2) ,pp: 109-122.

    ● Jing Wang, Jingyang Gao*. CNNdel: Calling Structural Variations on Low Coverage Data Based on Convolutional Neural Networks. BioMed Research International Volume 2017 (2017), Article ID 6375059, 8 pages.

    ● GUAN Rui, GAO Jing-yang*. Machine-learning-aided precise prediction of deletions with next-generation sequencing. Journal of Central South University. 2016.12.31,23(12):3239~3247.

    ● 高敬阳*.基于AdaBoost的基因组缺失变异综合检测策略. 东南大学学报(自然科学版),2014,44(5),pp924-928.(EI:201444132369).

    ● 张泽中,高敬阳*,吕纲,赵地.基于深度学习的胃癌病理图像分类方法. 计算机科学.2018,11,pp263-268.