师资队伍

陈建辉

电话:

E-mail:chenjianhui@bjut.edu.cn

通讯地址:北京工业大学材料楼

研究方向

脑信息学、Web智能、文本挖掘、知识增强的机器学习算法以及面向智慧医疗、智慧水务等领域的应用。

个人简介

男,讲师,清华大学/香港理工大学博士后,硕士生导师。20157月至今就职于北京工业大学信息科学技术学院从事教学科研工作。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。以第一作者或通讯作者发表SCI/EI论文40余篇;授权专利8项,授权软件著作权11项;参与编制国家/行业标准2项,专著2本。

教育简历

20069-20117月 北京工业大学计算机应用技术专业 博士研究生

工作履历

20157月至今就职于北京工业大学信息科学技术学院

学术兼职

CCF协同计算专业委员会委员

课程教学

主讲本科生课程《高级语言程序设计》、《高级语言程序设计实践训练》

科研项目

[1] 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

[2] 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。

[3] 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,2021-2022,主持

[4] 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

[5] 北京水科学技术研究院,典型供水公司和工业园区知识图谱构建及水效分析,2022-2023,参与

[6] 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,2020-2023,参与

[7] 北京市科委市区两级重大紧迫任务科技支撑项目,绿色智慧乡村关键技术与集成应用研究,2018-2020,参与

主要论文论著

[1] Shaofu Lin, Mengzhen Wang, Chengyu Shi, Zhe Xu, Lihong Chen, Qingcai Gao, Jianhui Chen*, MR-KPA: Medication Recommendation by Combining Knowledge-enhanced Pre-training with a Deep Adversarial Network. BMC Bioinformatics, 2022, 23:552, https://doi.org/10.1186/s12859-022-05102-1 (SCI, IF=3.307, JCR Q2) 

[2] 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, 2022. https://doi.org/10.1007/s11356-022-22769-4 (SCI, IF=5.190, JCR Q2)

[3] 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. https://doi.org/10.1186/s12859-022-04905-6 (SCI, IF=3.307, JCR Q2)

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

[5] 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 https://doi.org/10.1007/s12021-022-09571-w (SCI, IF=4.085, JCR Q2)

[6] 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. (SCI, IF=5.152, JCR Q2)

[7] 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)

[8] Ying ShengJianhui ChenXiaobo HeZhe XuJiangfan GaoShaofu Lin*: A Topic Learning Pipeline for Curating Brain Cognitive Researches. IEEE Access 8: 191758-191774 (2020) (SCI, IF=3.745, JCR Q1)

[9] Jianhui Chen, Jian Han, Yue Deng, Han Zhong, Ningning Wang, Youjun Li, Zhijiang Wan, Taihei Kotake, Dongsheng Wang and Ning 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)

[10] Shaofu Lin, Jiangfan Gao, Shun Zhang, Xiaobo He,Ying Sheng, Jianhui Chen*, A Continuous Learning Method for Recognizing Named Entities by Integrating Domain Contextual Relevance Measurement and Web Farming Mode of Web Intelligence, World Wide Web, 2020, 23(3): 1769-1790. (SCI, IF= 2.892, JCR Q2)

[11] Jianhui Chen, Jianhua Ma, Ning Zhong*, Yiyu Yao, Jiming Liu, Runhe Huang, Wenbin Li, Zhisheng Huang, Yan Gao, Jianping Cao. WaaS – wisdom as a service. IEEE Intelligent Systems, 2014, 29(6):40-47. (SCI, IF=1.815)

[12] Jianhui Chen and Ning Zhong. Toward the Data-Brain driven systematic brain data analysis, IEEE Transactions on Systems Man Cybernetics-Systems, 2013, 43(1): 222-228. (SCI)

[13] Ning Zhong and Jianhui 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. (SCI, IF=1.657)