个人简介

简萌，北京工业大学信息科学技术学院，校聘教授、硕士生导师。入选北京市优秀人才，北京市科协青年托举人才，北京工业大学新锐青年学者，北京工业大学日新人才。2015年毕业于西安电子科技大学电子工程学院智能感知与图像理解教育部重点实验室，获得模式识别与智能系统工学博士学位。2016年6月至2018年7月在北京工业大学电子科学与技术学科从事博士后研究工作。2018年11月至2019年11月在新加坡国立大学计算机学院LMS-NEXT++研究中心访学，从事社交多媒体分析、信息检索研究。主持10余项国家级、省部级科研项目。发表国内外著名期刊、会议论文87篇，获授权专利5项、软著1项。

主要研究方向

智能媒体计算

1） 图像、视频大数据多媒体内容分析

2） 社交多媒体用户个性化推荐

3） 信息检索与数据挖掘

主持的科研项目

1.国家自然科学基金面上项目，6217****

2.国家自然科学基金青年基金项目，6170****

3.北京市教委科研计划科技一般项目，KM2019****

4.北京市优秀人才培养资助青年骨干个人项目，2017****

5.中国博士后科学基金特别资助，2018****

6.中国博士后科学基金面上项目一等资助，2017****

7.北京市博士后科研活动经费资助，2017****

8.朝阳区博士后科研活动经费资助，2017****

9.北京工业大学“日新人才”培养计划，2018****

获奖情况

1.北京市优秀人才“青年骨干”

2.入选北京市科学技术协会青年人才托举工程

3.北京工业大学“日新人才”

4．中国博士后科学基金特别资助，全校仅获批7项

5.北京市科学技术奖技术发明二等奖

6.中国图象图形学学会技术发明二等奖

7. PRCV2021最佳论文提名奖

8.指导研究生获得爱奇艺人物识别挑战赛3等奖

9.北京工业大学研究生优秀硕士学位论文指导教师

10.北京工业大学本科特优毕业论文指导教师

11.北京工业大学本科优秀毕业论文指导教师

12.立德树人优秀班主任

社会与学术职务

1.电气与电子工程师协会IEEE、中国计算机学会CCF、中国图象图形学学会CSIG会员

2.CCF计算机视觉专委会CCFCV、CCF多媒体专委会CCFMM委员

3.国际顶会ACM Multimedia程序委员会成员

4.VALSE执行AC委员会EAAC领域主席

5.担任多个国际著名期刊、会议评阅人，包括IEEE Trans. Image Processing，IEEE Trans. Multimedia，Pattern Recognition，Neurocomputing，IEEE Trans. Automation Science & Engineering，ACM Multimedia，IEEE Int. Conf. Multimedia and Expo，Signal Processing: Image Communication，IET Image Processing，Multimedia Tools and Application

代表性论文

[1]Meng Jian, Langchen Lang, Jingjing Guo, Zun Li, Tuo Wang, Lifang Wu, Light Dual Hypergraph Convolution for Collaborative Filtering, Pattern Recognition, vol. 154, Oct. 2024. (SCI, IF: 8.0, JCR: Q1)

[2]Meng Jian, Yulong Bai, Xusong Fu, Jingjing Guo, Ge Shi*, Lifang Wu, Counterfactual Graph Convolutional Learning for Personalized Recommendation, ACM Transactions on Intelligent Systems and Technology, 2024. (SCI, IF: 10.8, JCR: Q2)

[3] Meishan Liu,Meng Jian, Yulong Bai, Jiancan Wu, and Lifang Wu*, Graph Contrastive Learning with Negative Propagation for Recommendation，IEEE Transactions on Computational Social Systems, 2024. (SCI, IF: 5.0, JCR: Q1)

[4]Meng Jian, Yulong Bai, Jingjing Guo, Lifang Wu*, Swarm Self-supervised Hypergraph Embedding for Recommendation, ACM Transactions on Knowledge Discovery from Data (TKDD), vol. 18, no. 4, pp. 1-19, 2024. (SCI, IF: 4.0, JCR：Q1, CCF-B,数据挖掘领域top期刊)

[5]Meng Jian, Tuo Wang, Shenghua Zhou, Langchen Lang, Lifang Wu, Compatible Intent-Based Interest Modeling for Personalized Recommendation, Applied Intelligence, vol. 53, pp. 27519–27536, 2023. (SCI, IF: 5.3, JCR：Q2)

[6] Meishan Liu,Meng Jian, Ge Shi, Lifang Wu*. Graph Contrastive Learning on Complementary Embedding for Recommendation, ACM SIGMM International Conference on Multimedia Retrieval (ACM ICMR 2023), Thessaloniki, Greece on June 12-15, 2023. (EI, CCF-B)

[7]Meng Jian, Chenlin Zhang, Meishan Liu, Xin Fu, Siqi Li, Ge Shi, Lifang Wu. Siamese Graph-Based Dynamic Matching for Collaborative Filtering, Information Sciences, vol. 611, pp. 185–198, 2022. (SCI, IF: 8.233, JCR: Q1)

[8]Meng Jian, Jingjing Guo, Ge Shi, Lifang Wu*, Zhangquan Wang, Multimodal Collaborative Graph for Image Recommendation, Applied Intelligence, vol. 53, pp. 560–573, 2022. (SCI, IF: 5.3, JCR：Q2)

[9]Meng Jian, Jingjing Guo, Chenlin Zhang, Ting Jia, Lifang Wu*, Xun Yang, Lina Huo, Semantic Manifold Modularization-based Ranking for Image Recommendation, Pattern Recognition, vol. 120, Dec. 2021. (SCI, IF: 8.518, JCR：Q1)

[10]Meng Jian, Cheolkon Jung*, Semi-Supervised Kernel Matrix Learning Using Adaptive Constraint-Based Seed Propagation,Pattern Recognition, vol. 112, Apr. 2021. (SCI, IF: 8.518, JCR：Q1)

[11]Meng Jian, Ting Jia, Xun Yang, Lifang Wu* and Lina Huo*. Cross-modal Collaborative Manifold Propagation for Image Recommendation, ACM SIGMM International Conference on Multimedia Retrieval (ACM ICMR 2019), 2019: 344-348. June 10-13 2019, Ottawa, Canada. (EI, CCF-B)

[12]Meng Jian, Shuai Zhang, Lifang Wu*, Shijie Zhang, Xiangdong Wang*, Yonghao He.Deep Key Frame Extraction for Sport Training, Neurocomputing, Vol. 328, No. 19, pp. 147-156, 2019.2.7. (SCI, IF: 4.438, JCR：Q1)

[13]Meng Jian*, Lifang Wu, Cheolkon Jung*, Qingtao Fu, Ting Jia.Visual saliency Estimation Using Constraints, Neurocomputing, vol. 290, pp. 1-11, 2018. (SCI, IF: 4.438, JCR：Q1)

[14]Meng Jian, Cheolkon Jung.Interactive image segmentation using adaptive constraint propagation,IEEE Transactions on Image Processing, Vol. 25, No. 3, pp. 1301-1311, 2016. (SCI, IF: 9.34,JCR：Q1, CCF-A)

[15]Meng Jian, Cheolkon Jung. Semi-supervised bi-dictionary learning for image classification with smooth representation-based label propagation,IEEE Transactions on Multimedia, Vol. 18, No. 3, pp. 458-473, 2016. (SCI, IF: 6.051, JCR：Q1, CCF-B)

[16]Meng Jian, Cheolkon Jung, Yanbo Shen. Interactive image retrieval using constraints,Neurocomputing,Vol. 161, No. 5, pp. 210 - 219, 2015. (SCI, IF: 4.438, JCR：Q1)

[17]Meng Jian, Cheolkon Jung, Yanbo Shen, Licheng Jiao, Juan Liu.Adaptive constraint propagation for semi-supervised kernel matrix learning,Neural Processing Letters,Vol. 41, No. 1, pp. 107-123, 2015. (SCI, IF: 2.891, JCR：Q3)

[18] Cheolkon Jung,Meng Jian, Juan Liu, Licheng Jiao, Yanbo Shen. Interactive image segmentation via kernel propagation,Pattern Recognition, Vol. 47, No. 8, pp. 2745-2755, 2014. (SCI, IF: 7.196, JCR：Q1)

[19]Meng Jian, Cheolkon Jung, Yaoguo Zheng. Discriminative structure learning for semantic concept detection with graph embedding,IEEE Transactions on Multimedia, Vol. 16, No. 2, pp. 413-426, 2014. (SCI, IF: 6.051, JCR：Q1) (CCF-B类期刊)

[20]Meng Jian, Cheolkon Jung.Class-discriminative kernel sparse representation-based classification using multi-objective optimization,IEEE Transactions on Signal Processing, Vol. 61, No. 18, pp. 4416-4427, 2013. (SCI, IF: 5.028, JCR：Q1)