简介: 罗廷金现任国防科技大学理学院副教授。于2018年获博士学位，已在顶级期刊或会议上发表40余篇学术论文，主要包括IEEE TPAMI，IEEE TKDE, IEEE TIP, IEEE TCYB, KDD, AAAI, ICME, PAKDD等。目前担任IEEE TIP、IEEE TKDE、中国科学等10余家国际权威期刊审稿人，并受邀担任ICML、IJCAI、AAAI、ICDM、ICPR等多个国际会议的PC Member。主持基础加强重点项目课题、国家自然科学基金等6项。获军队科技进步奖、中国系统工程学会优秀博士学位论文奖、湖南省优秀博士学位论文、学校秀青年创新奖等荣誉。入选湖南省湖湘青年英才计划和高层次卓越人才计划等。

Email: tingjinluo@hotmail.com
Follow me: DBLP   Researchgate   GitHub

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消息

  • 2024.03.15: 恭喜周浩等人的论文”结合对象属性识别的图像场景图生成方法研究”被中文核心期刊 _计算机科学_接收。

  • 2021.10.06: 恭喜周浩等人的论文”A Unified Deep Sparse Graph Attention Network for Scene Graph Generation”被JCR Q1期刊 _Pattern Recognition_接收。

  • 2021.08.27: 恭喜诸葛文章等人的论文”基于独立自表达学习的不完全多视图聚类方法”被CCF A类期刊 _中国科学: 信息科学_接收。

  • 2021.04.27: 恭喜孙宁朝等人的论文”Semi-supervised Learning with Label Proportion”被CCF A类期刊 _IEEE TKDE_接收。

  • 2021.03.06: 恭喜周浩等人的文章”Relationship-aware Primal-Dual Graph Attention Network for Scene Graph Generation”被会议 _ICME 2021_接收。

  • 2021.02.09: 恭喜汤西嘉等人的文章”Multiple Instance Learning for Unilateral Data” 被机器学习领域会议 _PAKDD 2021_接收。

研究岗位

  • 我的课题组目前有研究岗位若干，包括博士后、研究助理、博士、硕士等。如果您感兴趣，请将您的简历、成绩单、获奖证书、代表作发至我的邮箱。
  • 十分欢迎优秀的本科生（主要面向本校同学）来我的课题组参加科研训练和毕业设计！

招生信息

首先，非常欢迎考虑报考我的研究生！在给我写邮件之前，请您先仔细阅读下面的文字，并确认我们在科研观念和研究兴趣上一致:

研究兴趣：主要研究如何使用数学工具设计先进机器学习算法，并广泛应用于计算机视觉和数据挖掘等多个领域。 近期研究兴趣包括弱监督学习（如半监督学习、标签噪声鲁棒学习、多示例学习等）、多视图学习、因果学习等。

招生期望：希望能够招收数学基础好、编程能力强、英语功底扎实、擅于口头及书面表达的学生。有前期科研经历者加分（学术竞赛、论文发表、课外学术活动等）。同时也建议先学习过李宏毅老师的机器学习课程。

培养目标：经过精心组织的科研训练，使学生具备扎实的专业知识、缜密的科研思维、较强的动手能力、广阔的学术视野，及独立发现问题、思考问题、解决问题的重要科学素养； 在校期间在世界顶级期刊或会议上发表高水平、有影响力的论文，并有志于毕业后继续从事学术研究工作。

我的承诺：1）因我本人始终亲临科研一线，因此会在算法设计、代码编写、实验验证、论文撰写、专利申请、科研成果展示等给予你全方位的有效指导；2）提供浓厚的科研氛围、舒适的科研环境、丰厚的科研奖励、高效的运算设备；3）我几乎不会让你处理报账、递送材料、拿快递等与科研无关的行政事务，从而保证你有充足的、整块的科研时间；4）对于在顶会上发表论文的学生，会从学校参会资助和本人科研经费两方面积极资助你参会； 5）对于表现优秀的博士研究生，至少提供一次0.5-2年的海外访学联培机会；6）对于表现优秀的学生，我很乐意在毕业后给你推荐工作或深造机会。

学术论文

(*为同等贡献作者, #为通讯作者)

2024

  • 周浩，罗廷金，崔国恒. “基于对象属性识别的图像场景图生成方法研究”. 计算机科学, 2024, 录用. (CCF T2级中文期刊，SCI检索)

2021

  • Hao Zhou, Yazhou Yang, Tingjin Luo#, Jun Zhang#, Jun Lei, Shuohao Li, A Unified Deep Sparse Graph Attention Network for Scene Graph Generation, Pattern Recognition, 2021, Accepted. (JCR Q1期刊, CCF B类期刊) [PDF]

  • Hao Zhou, Tingjin Luo#, Jun Zhang, Jun Lei, Shuohao Li, “Relationship-aware Primal-Dual Graph Attention Network for Scene Graph Generation”, in IEEE International Conference on Multimedia and Expo (ICME), Shenzhen, China, July 5-9, 2021, Accepted. (CCF B类会议) [PDF]

  • Xijia Tang, Tingjin Luo#, Tianxiang Luan, Chenping Hou, “Multiple Instance Learning for Unilateral Data”, in Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021), Accepted, Delhi, India, 2021. (CCF C类会议) [PDF]

  • Xinyue Dong, Shilin Gu, Wenzhang Zhuge, Tingjin Luo, Chenping Hou#, “Active Label Distribution Learning”, Neurocomputing, vol. 436, pp. 12-21, 2021, DOI: 10.1016/j.neucom.2020.12.128. (CCF B类期刊, IF: 4.438) [PDF]

  • 诸葛文章，范瑞东，罗廷金，陶红，侯臣平，基于独立自表达学习的不完全多视图聚类方法，中国科学: 信息科学, 录用. (CCFA类中文期刊，SCI检索)

2020

  • Ruidong Fan, Tingjin Luo, Wenzhang Zhuge, Sheng Qiang, Chenping Hou#, “Multi-view Subspace Learning via Bidirectional Sparsity”, Pattern Recognition, 108: 107524, 2020, DOI: 10.1016/j.patcog.2020.107524, (CCF B期刊, IF: 7.196). [PDF][Code]

  • Tianxiang Luan, Tingjin Luo, Wenzhang Zhuge, Chenping Hou#, “Optimal Representative Distribution Margin Machine for Multi-Instance Learning”, IEEE Access, vol. 8, pp. 74864-74874, 2020, DOI: 10.1109/ACCESS.2020.2988764. (IF: 3.745). [PDF]

  • Wenzhang Zhuge, Tingjin Luo, Hong Tao, Chenping Hou#, Dongyun Yi, “Multi-View Spectral Clustering With Incomplete Graphs”, IEEE Access, vol. 8, pp. 99820-99831, 2020, DOI: 10.1109/ACCESS.2020.2997755. (IF: 3.745) [PDF]

  • Wenzhang Zhuge, Hong Tao, Tingjin Luo, Linli Zeng, Chenping Hou#, Dongyun Yi, “Joint Representation Learning and Clustering: A Framework for Grouping Partial Multiview Data”, IEEE Transactions on Knowledge and Data Engineering, accepted, DOI: 10.1109/TKDE.2020.3028422. (CCF A类期刊, IF: 4.935) [PDF]

2019

  • Tingjin Luo, Chenping Hou#, Feiping Nie, Dongyun Yi, “Dimension Reduction for Non-Gaussian Data by Adaptive Discriminative Analysis”, IEEE Transactions on Cybernetics, vol. 49, no. 3, pp. 933-946, March 2019, DOI: 10.1109/TCYB.2018.2789524. (JCR Q1期刊, IF: 11.079) [PDF]

  • Zhipeng Lin, Zhenyu Zhao, Tingjin Luo#, Wenjing Yang, Yongjun Zhang, Yuhua Tang, “Non-Convex Transfer Subspace Learning for Unsupervised Domain Adaptation”, Proceedings of IEEE International Conference on Multimedia and Expo (ICME 2019), Shanghai, China, 2019, pp. 1468-1473, DOI: 10.1109/ICME.2019.00254, EI: 20193407349323. (CCF B类会议) [PDF]

  • Haotian Wang, Wenjing Yang#, Zhenyu Zhao, Tingjin Luo, Ji Wang, Yuhua Tang, “Rademacher Dropout: An Adaptive Dropout for Deep Neural Network via Optimizing Generalization Gap”, Neurocomputing, vol. 357, pp. 177-187, 2019, DOI: 10.1016/j.neucom.2019.05.008. (CCF B类期刊, IF: 4.438) [PDF]

  • Haodong Yang, Jun Zhang#, Shuohao Li#, Tingjin Luo, “Bi-direction Hierarchical LSTM with Spatial-Temporal Attention for Action Recognition”, Journal of Intelligent & Fuzzy Systems, vol.36, no. 1, pp. 775-786, 2019, DOI: 10.3233/JIFS-18209. (IF: 1.851) [PDF]

2018

  • Tingjin Luo, Chenping Hou#, Feiping Nie, Hong Tao, Dongyun Yi, “Semi-Supervised Feature Selection via Insensitive Sparse Regression with Application to Video Semantic Recognition”, IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 10, pp. 1943-1956, 2018, DOI: 10.1109/TKDE.2018.2810286, WOS:000444603900009. (CCF A类期刊, IF: 4.935) [PDF]

  • Weizhong Zhang*, Tingjin Luo*, Shuang Qiu, Jieping Ye, Deng Cai, Xiaofei He, Jie Wang#, “Identifying Genetic Risk Factors for Alzheimer’s Disease via Shared Tree-Guided Feature Learning Across Multiple Tasks”, IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 11, pp. 2145-2156, 2018, DOI: 10.1109/TKDE.2018.2816029, WOS:000446795900010. (CCF A类期刊, IF: 4.935) [PDF]

  • Gongmin Lan, Chenping Hou#, Feiping Nie, Tingjin Luo, Dongyun Yi, “Robust feature selection via simultaneous capped norm and sparse regularizer minimization”, Neurocomputing, vol. 283, pp. 228-240, 2018, DOI: 10.1016/j.neucom.2017.12.055, WOS:000424896600021. (CCF B类期刊, IF: 4.438) [PDF]

2017

  • Tingjin Luo, Weizhong Zhang, Shuang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye#, Jie Wang#, “Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning”, Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2017), Halifax, Canada, August 2017, pp. 345-354, DOI: 10.1145/3097983.3097984, EI: 20173704157018. (CCF A类会议) [PDF]

  • Yang Yang*, Tingjin Luo*, Zhoujun Li, Xiaoming Zhang, Philip S. Yu, “A Robust Method for Inferring Network Structures”, Scientific Reports, vol. 7, no. 5221, pp. 1-12, 2017, DOI: 10.1038/s41598-017-04725-2, WOS:000405425000025. (JCR Q2期刊, IF: 4.576)[PDF]

  • Chenping Hou, Yuanyuan Jiao, Feiping Nie, Tingjin Luo, Zhi-Hua Zhou#, “2D Feature Selection by Sparse Matrix Regression”. IEEE Transations on Image Processing, vol. 26, no. 9, pp. 4255-4268, 2017, DOI: 10.1109/TIP.2017.2713948, WOS:000405395900001. (CCF A类期刊, IF: 9.340) [PDF]

  • Guangtao Wang, Jiayu Zhou, Jingjie Ni, Tingjin Luo, Wei Long, Hai Zhen, Gao Cong, Jieping Ye#, “Robust Self-Tuning Sparse Subspace Clustering”, Procedings of 17th IEEE International Conference on Data Mining Workshops (ICDMW 2017), pp.858-865, New Orleans, USA, 2017, DOI: 10.1109/ICDMW.2017.117, WOS:000425845700114. [PDF]

2017以前

  • Tingjin Luo, Chenping Hou#, Dongyun Yi, Jun Zhang, “Discriminative orthogonal elastic preserving projections for classification”, Neurocomputing, vol. 179, pp. 54-68, 2016, DOI: 10.1016/j.neucom.2015.11.037, WOS:000370090300005. (CCF B类期刊, IF: 4.438) [PDF]

  • Tingjin Luo, Jun Zhang, Lin Lian, “Speed up junction detector based on azimuth consensus by Harris corner”, Optical Review, vol. 21, no. 2, pp. 135-142, Mar. 2014, DOI: 10.1007/s10043-014-0021-1, WOS:000334253000005. (IF: )

  • Jun Zhang, Tingjin Luo#, Gui Gao, Lin Lian, “Junction Point Detection Algorithm for SAR Image”, International Journal of Antennas and Propagation, vol. 2013, pp. 1-9, Mar. 2013, DOI: 10.1155/2013/357379, WOS:000317567100001. (IF: 1.207) [PDF]

  • Jun Zhang, Weiqiang Huang, Tingjin Luo, “3D Reconstruction of Periodic Human Walking Trajectories Based on Single View”, Chinese Journal of Electronics, vol. 22, no. 3, pp.455-460, July 2013, WOS:000321481000004. (JCR Q4, IF: 0.941)

  • Jun Zhang, Shukui Xu, Kuihua Huang, Tingjin Luo, “Accurate Moving Target Detection Based on Background Subtraction and SUSAN”, International Journal of Computer and Electrical Engineering, vol. 4, no. 4, pp.436-439, Aug. 2012, DOI: 10.7763/IJCEE.2012.V4.529, WOS:000321481000004. [PDF]

工作经历

  • 06/2022-至今：副教授，国防科技大学理学院应用数学研究中心
  • 12/2020-2022.06：副教授，国防科技大学文理学院体系科学系
  • 06/2018-12/2020: 助理讲授, 国防科技大学文理学院数学系

获奖情况

  • 中国系统工程学会优秀博士学位论文奖，0/2020
  • 湖南省优秀博士学位论文，08/2020

报告

  • 10/2020: “基于非凸稀疏优化的鲁棒多示例学习方法”, 中国系统工程学会第21届学术年会 2020, 中国陕西西安, 大会报告
  • 01/2019: “高维数据特征分析方法”, 学校量子交叉学术年会 2018, 中国湖南长沙, 小组报告
  • 08/2017: “Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning”, ACM KDD 2017, 加拿大哈利法克斯, 大会报告

联系方式

通讯地址： 湖南省长沙市开福区福元路一号国防科技大学文理学院体系科学系 邮政编码： 410073 办公地址： 国防科技大学文理学院4201A室