[1] 200901-201308 俄亥俄州立大学 博士研究生

[2] 200609-200901 清华大学 硕士研究生

[3] 200209-200607 清华大学 大学本科

[1] 202407-至今 教授 南昌大学人工智能学院

[2] 201308-202406 高级研究员 美国高通研究院

赣鄱英才计划-创新领军人才青年项目

商用洗碗机餐具摆筐质量检测系统

基于物联网智慧校园管理平台设计与实现

[1] Jingtian Zhou; Zhuzhu Zhang; May Wu; Hanqing Liu; Yan Pang; Anna Bartlett; Zihao Peng; Will N. Lagos; Elora Williams; Cheng-Ta Lee; Paula Assakura Miyazaki; Andrew Aldridge; Qiurui Zeng; J. L. Angelo Salinda; Naomi Claffey; Michelle Liem; Conor Fitzpatrick; Lara Boggeman; Zizhen Yao; Shengbo Chen; et al. Brain-wide correspondence of neuronal epigenomics and distant projections, Nature, 2023, 624(7991): 355-365.

[2] Shu, Xu-Jun; Chang, Hui; Wang, Qun; Chen, Wu-Gang; Zhao, Kai; Li, Bo-Yuan; Sun, Guo-Chen; Chen, Sheng-Bo*; Xu, Bai-Nan. Deep Learning model-based approach for preoperative prediction of Ki67 labeling index status in a noninvasive way using magnetic resonance images: A single-center study[J]. Clinical Neurology and Neurosurgery, 2022, 219: 107301.

[3] Zhao, Kai;Li, Boyuan;Zhang, Kai;Liu, Ruoyu;Gao, Long；Shu, Xujun；Liu, Minghang；Yang, Xuejun；Chen, Shengbo*；Sun, Guochen. Automatic 1p/19q co-deletion identification of gliomas by MRI using deep learning U-net network[J]. Computers and Electrical Engineering, 2023, 105: 108482.

[4] Hui Chang, Kai Zhao, Jun Qiu, Xiang-jun Ji, Wu-gang Chen, Bo-yuan Li, Cheng Lv,Zi-cheng Xiong,Sheng-bo Chen*, Xu-jun Shu. Prediction of intraoperative cerebrospinal fluid leaks in endoscopic endonasal transsphenoidal pituitary surgery based on a deep neural network model trained with MRI images: a pilot study[J]. Frontiers in Neuroscience, 2023, 17: 1203698.

[5] Yue, Ling, Wugang Chen, Saichao Liu, Shengbo Chen* and Shi-fu Xiao. An explainable machine learning based prediction model for Alzheimer's disease in China longitudinal aging study[J]. Frontiers in aging neuroscience, 2023, 15: 1267020.

[6] Cheng Lv, Xujun Shu, Hui Chang, Jun Qiu, Shuo Peng, Keping Yu, Shengbo Chen∗and Hong Rao*. Classification of high-grade glioblastoma and single brain metastases using a new SCAT-inception model trained with MRI images[J]. Frontiers in Neuroscience, 2024, 18: 1349781.

[7] Zicheng Xiong, Kai Zhao, Like Ji, Xujun Shu, Shengbo Chen*, and Fuxing Yang*. Multi-modality 3D CNN Transformer for Assisting Clinical Decision in Intracerebral Hemorrhage[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland, 2024: 522-531.

[8] Zicheng Xiong, Qiu Jun, Quan Liang, Jingcheng Jiang, Kai Zhao, Hui Chang, Cheng Lv, Wanjun Zhang, Boyuan Li, Jingbo Ye, Shangbo Li, Shuo Peng, Changrong Sun, Shengbo Chen*, Dazhi Long, and Xujun Shu*. Deep learning models for rapid discrimination of high-grade gliomas from solitary brain metastases using multi-plane T1-weighted contrast-enhanced (T1CE) images[J]. Quantitative Imaging in Medicine and Surgery, 2024, 14(8): 5762.

[9] Wenbin Wei, Zhonghao Yao, Zicheng Xiong, Shuo Peng, Shengbo Chen*. Deep Learning-based Segmentation and Discrimination of High-grade Gliomas and Solitary Metastatic Tumors[C]//Proceedings of the International Conference on Algorithms, Software Engineering, and Network Security. 2024: 700-704.

[10] Cheng Lv, Xu-Jun Shu, jun Qiu, Zi-cheng Xiong, Jing bo Ye, Shang bo Li, Sheng-Bo Chen*, Hong Rao. MamTrans: magnetic resonance imaging segmentation algorithm for high-grade gliomas and brain meningiomas integrating attention mechanisms and state-space models[J]. Quantitative Imaging in Medicine and Surgery, 2025, 15(6): 5796.

[11] Cheng Lv，Xu-Jun Shu，Quan Liang，jun Qiu ，Zi-Cheng Xiong ，Jing bo Ye，Shang bo Li，Cheng Qing Liu1，Jing Zhen Niu5，Sheng-Bo Chen*，Hong Rao*. BrainTumNet: multi-task deep learning framework for brain tumor segmentation and classification using adaptive masked transformers[J]. Frontiers in Oncology, 2025, 15: 1585891.

[12] Cheng Lv, Xu‐Jun Shu, jun Qiu, Zi‐cheng Xiong, Jing bo Ye, Shang bo Li, Sheng‐Bo Chen*, Hong Rao. AI‐enabled precise brain tumor segmentation by integrating Refinenet and contour‐constrained features in MRI images[J]. Medical Physics, 2025, 52(7): e17958.

[13] Gang Luo, Hong Rao, Panfeng An, Yunxia Li, Ruiyun Hong, Wenwu Chen, Shengbo Chen*. Exploring adaptive graph topologies and temporal graph networks for EEG-based depression detection[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023, 31: 3947-3957.

[14] Renxi Guo, Hong Rao, Shengbo Chen*, Gang Luo, Panfeng An, Wenying Duan. Channel-adaptive graph convolution based temporal encoder network for EEG emotion recognition[C]//Proceedings of the annual meeting of the cognitive science society. 2024, 46.

[15] Zuolong Zhang, Xin He, Dazhi Long, Gang Luo, Shengbo Chen*. Enhancing Generalizability and Performance in Drug-Target Interaction Identification by Integrating Pharmacophore and Pre-trained Models[C]//Proceedings International Society for Computational Biology (ISMB).2024.

[16] Zuolong Zhang, Xin He, Dazhi Long, Gang Luo, Shengbo Chen*. Enhancing generalizability and performance in drug–target interaction identification by integrating pharmacophore and pre-trained models[J]. Bioinformatics, 2024, 40(Supplement_1): i539-i547.

[17] Zuolong Zhang, Gang Luo, Yixuan Ma, Zhaoqi Wu, Shuo Peng, Shengbo Chen* & Yi Wu*. GraphkmerDTA: integrating local sequence patterns and topological information for drug-target binding affinity prediction and applications in multi-target anti-Alzheimer’s drug discovery[J]. Molecular Diversity, 2025: 1-18.

[18] Zuolong Zhang, Fang Liu, Xiaonan Shang, Shengbo Chen*, Fang Zuo, Yi Wu, Dazhi Long. ComNet: A Multiview Deep Learning Model for Predicting Drug Combination Side Effects[J]. Journal of Chemical Information and Modeling, 2025, 65(2): 626-639.