研究方向
音乐生成、多模态情感计算

个人荣誉
优秀博士奖学金、AZFT优秀实习生、优秀团干部（担任班级团支书）、优秀研究生、优秀三好学生

主要成果
悟韵音乐生成系统、阿里巴巴音乐素材库
音乐生成相关论文：
2022 Kejun Zhang†, Xinda Wu†, Tieyao Zhang, Zhijie Huang, Xu Tan, Qihao Liang, Jiaxing Yu, Songruoyao Wu, Chongjun Zhong, Xiaoyu Chen, Rui Zhang,Lingyun Sun*, “WuYun: Exploring knowledge-enhanced hierarchical skeleton-guided melody generation using deep learning,” (论文修改中）
2020 Baixi Xing, Xiang Zhang, Kejun Zhang, Xinda Wu, Hui Zhang, Jun Zheng, Lekai Zhang, & Shouqian Sun. (2020), “Popmash: an automatic musical-mashup system using computation of musical and lyrical agreement for transitions.” Multimedia Tools and Applications, 79(12).
情感计算相关论文：
2022 Xiaoyu Chen, Shouqian Sun, Ziqi Zhang, Zirui Ma, Xinda Wu, Hongbo Li, Tianrun Chen, and Kejun Zhang, “Consumer shopping emotion and interest database: a unique database with a multimodal emotion recognition method for retail service robots to infer consumer shopping intentions better than humans,” Journal of Electronic Imaging 31(6), 061807 (18 May 2022). https://doi.org/10.1117/1.JEI.31.6.061807
2021 Kejun Zhang, Xinda Wu, Xinghang Xie, Xiaoran Zhang, Hui Zhang., Xiaoyu Chen., and Lingyun Sun*, “Werewolf-XL: A Database for Identifying Spontaneous Affect in Large Competitive Group Interactions,” in IEEE Transactions on Affective Computing, doi: 10.1109/TAFFC.2021.3101563. (IF=13.99, SCI一区，中国科协T1，情感计算领域顶刊)
2021 Kejun Zhang, Xinda Wu, Ruiyuan Tang, Qiaoqiao Huang, Changyuan Yang, Hui Zhang, “The JinYue Database for Huqin Music Emotion, Scene and Imagery Recognition.” 2021 IEEE 4th International Conference on Multimedia Information Processing and Retrieval (MIPR), 2021, pp. 314-319, doi: 10.1109/MIPR51284.2021.00059.

2019        Baixi Xing, Kejun Zhang, Lekai Zhang, Xinda Wu, Jian Dou, & Shouqian Sun. (2019), “Image–Music Synesthesia-Aware Learning Based on Emotional Similarity Recognition.” IEEE Access, 7, 136378-136390.

2019        Baixi Xing, Hui Zhang, Kejun Zhang, Lekai Zhang, Xinda Wu, Xiaoying Shi, Shanghai Yu, & Sanyuan Zhang. (2019). “Exploiting EEG Signals and Audiovisual Feature Fusion for Video Emotion Recognition.” IEEE Access, 7, 59844-59861.