Name:Xue Feng 

Professional Title:Professor

Situation of Tutors:Supervisor of Doctorate Candidates & Supervisor of Master's Candidates

School/Department: School of Software

Personal Profile:

Xue Feng, a professor and doctoral supervisor at Hefei University of Technology. He has been engaged in research on artificial intelligence, multimodal big data analysis, and intelligent recommendation systems for an extended period. Professor Xue has led 4 projects funded by the National Natural Science Foundation (including 3 general projects and 1 youth fund), as well as various research projects such as the Anhui Natural Science Foundation and the Major Science and Technology Special Project of Anhui Province, totaling more than 30 projects. He has served as the first author (corresponding author) for over 40 academic papers published in journals and conferences including TMM (Chinese Academy of Sciences Zone 1), TOIS (CCF-A), TCSVT, ACM TOMM (CCF-B), IEEE TCSS (IF=6), Information Science (Chinese Academy of Sciences Zone 1), IEEE Multimedia (JCR Zone 1). These papers cover areas such as multimedia processing and recommendation systems, and he holds 8 granted patents in these domains.

Professor Xue Feng was selected as one of the seventh batch of leading innovative and entrepreneurial talents in Anhui Province (Special Plan) and is the leader of the industrial innovation team in Hefei City (Artificial Intelligence). The personalized recommendation algorithm DeepICF proposed by the applicant (published in the top-tier journal ACM TOIS in the field of information retrieval in 2019, with the paper published for 3 years and cited over 280 times on Google Scholar) won the second place in the 2018 Mobile Knowledge Sharing Platform Recommendation Algorithm Online Evaluation Competition (co-organized by Zhihu Company and Tsinghua University). He was also awarded the Best Paper Award at the China Multimedia Conference in 2020.

Professor Xue Feng is the head of the Software Engineering discipline at Hefei University of Technology. Additionally, he is a member of the Computer Vision Committee and Multimedia Committee of the China Computer Society, a member of the Hefei Big Data Industry Alliance Expert Committee, and an evaluation expert for the review panel of the National Natural Science Foundation and the National Science and Technology Award.

Research Directions and Achievements:

1.Visual Multimedia Analysis:

This research direction involves the integration of theoretical study with practical engineering applications. Key research topics include target detection, defect detection, and lip reading, addressing typical problems in computer vision. Research outcomes in this area have been published in high-profile conferences and journals such as TMM, TCSVT, and TOMM. Developed systems have been applied within multiple enterprises.

2.Intelligent Recommendation Systems:

The primary theoretical focus of Professor Xue's team is on intelligent recommendation systems. Research within this domain includes multimedia recommendation and recommendation systems based on causal assumptions. Notable achievements in this field have been published in high-impact international journals and conferences such as TOIS, TCSS, and SIGIR. The proposed DeepICF personalized recommendation algorithm, published in the top-tier journal ACM TOIS in 2019, has garnered significant attention with 287 citations on Google Scholar. It also secured the second position in the 2018 Mobile Knowledge Sharing Platform Recommendation Algorithm Online Evaluation Competition (co-organized by Zhihu Company and Tsinghua University).

3.JavaEE Information System Development:

This research direction is geared towards meeting the needs of enterprises and institutions. It involves the development and design of information systems using advanced JavaEE technology. Aligned with Professor Xue's undergraduate course "Java Language Programming," this direction has successfully completed over 10 commissioned projects from various organizations.

Representative Academic Papers:

[1] Feng Xue*, Xiangnan He, Xiang Wang, Jiandong Xu, Kai Liu, and Richang Hong. 2019. Deep Item-based Collaborative Filtering for Top-N Recommendation, ACM Transactions on Information Systems, 2019, 37(3): 1-25.  (CCF-A, 287 Google citations, highly cited paper)

[2] Liu, Kang, Feng Xue*, Dan Guo, Le Wu, Shujie Li and Richang Hong. 2023. MEGCF: Multimodal Entity Graph Collaborative Filtering for Personalized Recommendation. ACM Transactions on Information Systems. ACM Transactions on Information Systems 41, 2 (2023), 1-27. (CCF A)

[3] Shuaiyang Li, Dan Guo, Kang Liu, Richang Hong, and Feng Xue*. 2023. Multimodal Counterfactual Learning Network for Multimedia-based Recommendation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2023, 1-10. July 23–27, 2023, Taipei, Taiwan of China. (SIGIR, CCF A)

[4] Feng Xue, Tian Yang, Kang Liu, Zikun Hong, Mingwei Cao, Dan Guo and Richang Hong. 2023. LCSNet: End-to-End Lipreading with Channel-Aware Feature Selection. ACM Transactions on Multimedia Computing, Communications, and Applications. 19, 1s 2023, 1-21. (CCF B)

[5] Liu, Kang, Feng Xue*, Dan Guo, Peijie Sun, Shengsheng Qian and Richang Hong. 2023. Multimodal Graph Contrastive Learning for Multimedia-Based Recommendation. IEEE Transactions on Multimedia. 2023, 1-13. (SCI 1，CCF B，TOP)

[6] Feng Xue，Richang Hong*，Xiangnan He，Jianwei Wang，Shengsheng Qian，Changsheng Xu. Knowledge-Based Topic Model for Multi-Modal Social Event Analysis. IEEE Transactions on Multimedia. 22, 8 2019, 2098-2110. (SCI 1，CCF B，TOP)

[7] Feng Xue, Yu Li, Deyin Liu, Yincen Xie, Lin Wu, Richang Hong. 2023. LipFormer: Learning to Lipread Unseen Speakers Based on Visual-Landmark Transformers. IEEE Transactions on Circuits and Systems for Video Technology, 9(2023), 4507 - 4517 (CCF B，TOP)

[8] Naiyang Miao, Feng Xue*, and Richang Hong; Multi-Modal Semantics-Based Supervised Latent Dirichlet Allocation for Event Classication, in IEEE MultiMedia, vol., no. 01, pp. 1-1, 5555.doi: 10.1109/MMUL.2021.3077915. （ChinaMM2020, Best Paper Award）

Some Granted Patents:

[1] 薛峰，杨添，王文博，洪自坤，融合通道注意力和选择性特征融合机制的唇语识别方法，2022年09月16日，ZL202110366767.6

[2] 薛峰，郭昊，李宏博，储德军，谢胤岑，基于通道注意力与时间卷积网络的句子级唇语识别方法，2023年04月07日，ZL202210348821.9

[3] 薛峰，王文博，洪日昌，曾涛，融合有监督信息的基于矩阵分解的跨模态哈希检索方法，2021-8-17，ZL202010049715.1

[4] 薛峰，周文杰，洪自坤，盛一城，一种融合知识图谱和用户交互的图模型智能商品推荐方法，2022-09-13，ZL202110612686.X

[5] 薛峰，董浩，贾伟，顾靖，罗月童，雍城西，一种基于人脸特征和掌纹特征融合的身份识别方法，2016年04月06日，ZL 201510112185.X

[6] 薛峰，顾靖，董浩，贾伟，罗月童，一种基于特征富集区域集合的图像检索方法，2016

Research Projects:

[1] National Natural Science Foundation of China (General Project), Multimedia Recommendation based on User Preference Feature Mining and Multimodal Collaborative Knowledge Graph (No. 62272143), Jan 2023 - Dec 2026 (Principal Investigator).

[2] National Natural Science Foundation of China (General Project), Key Issues in Multimodal, Cross-Platform, Large-Scale Social Media Event Analysis (No. 61772170), Jan 2018 - Dec 2021 (Principal Investigator).

[3] National Natural Science Foundation of China (General Project), Research on Camouflage Evaluation Model and Detection Method Based on Visual Attention Mechanism (No. 61472115), Jan 2015 - Dec 2018 (Principal Investigator).

[4] National Natural Science Foundation of China (Young Scientists Fund), Research on Three-Dimensional Texture Deformation Method to Maintain Spatiotemporal Continuity (No. 61202283), Jan 2013 - Dec 2015 (Principal Investigator).

[5] Major Special Project of Anhui Province, Key Technology Research and Development and Industrialization of Intelligent Taxation Service Platform based on Multimodal Big Data Fusion (No. 202203a05020025), May 2022 - Apr 2025 (Project Collaborator, Unit Responsible).