陈建辉，男，清华大学/香港理工大学博士后，副教授，硕士生导师。2011年7月毕业于2138cc太阳集团计算机应用技术专业，获工学博士学位。2015年7月至今就职于2138CC太阳集团从事教学科研工作。主讲课程《高级语言程序设计》、《高级语言程序设计实践训练》、《人工智能导论》、《Web智能》，获得2138cc太阳集团优秀班主任。曾就职于华大基因研究中心、工信部赛迪研究院以及江苏万维艾斯网络智能产业创新中心有限公司、北京信广华科技有限公司等。

主要研究方向为脑信息学、Web智能、文本挖掘、知识增强的机器学习及其在智慧医疗、智慧水务等领域的应用。以第一作者或通讯作者在《IEEE Transactions on Knowledge and Data Engineering》、《IEEE Transactions on Systems, Man, and Cybernetics: Systems》、《IEEE Intelligent Systems》、《IEEE Transactions on Cloud Computing》、《Information Fusion》、《Environmental Science and Pollution Research》、《IEEE Transactions on Computational Social Systems》、《AdvancedScience》、《IEEE Transactions on Emerging Topics in Computational Intelligence》等国际期刊发表论文40余篇，授权国际国内专利14项，软件著作权11项；参与编制国家/行业标准2项，专著2本。

主要科研项目

[1]基于大模型的某环境影响算法集成训练技术开发项目，2025-2026，主持

[2]北京水科学技术研究院，暴雨洪涝舆情数据库构建与分析，2024-2025，主持

[3]北京市自然科学基金面上项目,面向系统化脑认知研究的数据溯源构建，2022-2024，主持

[4]北京水科学技术研究院，北京市多水源、多层次水资源配置知识图谱构建及应用，2022-2023，主持。

[5]上海宝信软件股份有限公司北京分公司，ACP100事故风险统计分析模块开发，2021-2024，主持

[6]北京市教委科技计划一般项目,面向脑认知大数据的数据起源构建,2017-2019,主持

[7]国家重点研发计划，宜居城市全域联动认知计算关键技术研究与系统研发，2020-2024，参与

代表性科研成果

[1]Lianfang Ma#, Jianhui Chen#, Jiajin Huang, Yiyu Yao*, and Ning Zhong*, Event Causal Relation Extraction in Brain Connectomics: A Model Utilizing Weighted Joint Constrained Learning,IEEE Transactions on Emerging Topics in Computational Intelligence, 2025, 9(2):1885-1896. doi:10.1109/TETC1.2024.3462173 (共同第一作者,SCI,IF=5.3, JCR Q1)

[2] Lin, S., Zhou, S., jiao, H.et al. CDR-Detector: Achronic disease risk prediction model combining pre-training with deep reinforcement learning,Complex & Intelligent Systems, 2025, 11, 104. doi:10.1007/s40747-024-01697-5(通讯作者,SCI, IF=4.6, JCR Q2)

[3] Hongzhi Kuai#,Jianhui Chen#, Xiaohui Tao, Lingyun Cai, Kazuyuki lmamura, Hiroki Matsumoto, Peipeng Liang*, Ning Zhong*, Never-Ending Learning for Explainable Brain Computing.AdvancedScience, 2024,11, 24. doi:10.1002/advs.202307647 (共同第一作者, SCI, IF=14.3, JCR Q1)

[4]Mi Li, Yuqi Wang, Chuang Yang, Zeying Lu,Jianhui Chen*,Automatic Diagnosis of Depression Based on Facial Expression Information and Deep Convolutional Neural Network.IEEE Transactions on Computational Social Systems,2024, 11, 5.doi:10.1109/TCSS.2024.3393247(通讯作者,SCI, IF=4.5, JCR Q1)

[5] Jianzhuo Yan, Qingcai Gao, Yongchuan Yu, Lihong Chen, Zhe Xu,Jianhui Chen*,Combining Knowledge Graph with Deep Adversarial Network for Water Quality Prediction.Environmental Science and Pollution Research, 2023,30:10360-10376. doi:10.1007/s11356-022-22769-4(通讯作者,SCI, IF=5.190, JCR Q1)

[6]Shaofu Lin, Mengzhen Wang, Chengyu Shi, Zhe Xu, Lihong Chen, Qingcai Gao,Jianhui Chen*,MR-KPA:MedicationRecommendation by Combining Knowledge-enhanced Pre-training with a DeepAdversarialNetwork.BMC Bioinformatics,2022, 23:552.doi:10.1186/s12859-022-05102-1(通讯作者,SCI, IF=3.307, JCR Q2)

[7] Shaofu Lin, Chengyu Shi,Jianhui Chen*, GeneralizedDTA: Combining Pre‑training and Multi‑task Learning to Predict Drug‑target Binding Affinity for Unknown Drug Discovery.BMC Bioinformatics, 2022, 23:367. doi:10.1186/s12859-022-04905-6(通讯作者,SCI, IF=3.307, JCR Q2)

[8]Jianzhuo Yan, Lihong Chen, Yongchuan Yu, Hongxia Xu,Jianhui Chen*,EmergEventMine: End-to-end Chinese Emergency Event Extraction Using aDeep Adversarial Network.ISPRS International Journal of Geo-Information,2022, 11(6):345.doi:10.3390/ijgi11060345(通讯作者,SCI, IF=3.099, JCR Q2)

[9]Jianzhuo Yan, Lihong Chen, Yongchuan Yu, Hongxia Xu, Zhe Xu, Ying Sheng,Jianhui Chen*, Neuroimaging-ITM: A Text Mining Pipeline Combining Deep Adversarial Learning with Interaction Based Topic Modeling for Enabling the FAIR Neuroimaging Study.Neuroinformatics, 2022,doi:10.1007/s12021-022-09571-w(通讯作者,SCI, IF=4.085,JCRQ2)

[10] Shaofu Lin, Zhe Xu, Ying Sheng, Lihong Chen,Jianhui Chen*, AT-NeuroEAE: A Joint Extraction Model of Events with Attributes for Research Sharing-Oriented Neuroimaging Provenance Construction.frontiers in Neuroscience, 2022, 15:739535. doi:10.3389/fnins.2021.739535.(通讯作者,SCI, IF=5.152, JCR Q2)

[11] Hongzhi Kuai, Ning Zhong*,Jianhui Chen, Yang Yang, Xiaofei Zhang, Peipeng Liang*, Kazuyuki Imamura, Lianfang Ma, Haiyuan Wang, Multi-source Brain Computing with Systematic Fusion for Smart Health.Information Fusion, 2021, 75: 150-167.(SCI, IF=17.564, JCR Q1)

[12]Ying Sheng,Jianhui Chen,Xiaobo He,Zhe Xu,Jiangfan Gao,Shaofu Lin*: A Topic Learning Pipeline for Curating Brain Cognitive Researches.IEEE Access 8: 191758-191774 (2020)(SCI, IF=3.745, JCR Q1)

[13]Jianhui Chen, Jian Han, Yue Deng, Han Zhong, Ningning Wang, Youjun Li, Zhijiang Wan, Taihei Kotake, Dongsheng Wang andNing Zhong*, Wisdom as a Service for Mental Health Care.IEEE Transactions on Cloud Computing, 2020, 8(2):539-552.(SCI, IF=4.714, JCR Q1)

[14]Jianhui Chenand Ning Zhong. Toward the Data-Brain Driven Systematic Brain Data Analysis.IEEE TransactionsonSystems Man Cybernetics-Systems, 2013, 43(1): 222-228. (SCI,JCRQ1)

[15] Ning Zhong andJianhui Chen*. Constructing a New-style Conceptual Model of Brain Data for Systematic Brain Informatics.IEEE Transactions on Knowledge and Data Engineering, 2012, 24(12): 2127-2142.(通讯作者,SCI, IF=1.657,JCRQ1)

联系方式

E-mail: chenjianhui@bjut.edu.cn