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个人简介

韩特,现就职于北京理工大学管理与经济学院/能源与环境政策研究中心,预聘副教授、特别研究员、博士生导师。主要研究方向包括复杂系统智能运维管理、智慧能源管理、科学机器学习、人工智能与工程管理等。在国际高水平期刊或会议上发表论文50余篇,入选ESI高被引论文8篇,ESI热点论文2篇,曾获清华大学水木学者、清华大学优秀博士学位论文、中国运筹学会运筹应用奖等荣誉。《Journal of Risk and Reliability》、《Measurement Science and Technology》等国际SCI期刊客座编辑。主持国家自然科学基金1项、中国博士后科学基金特别资助1项、中国博士后科学基金面上资助1项,作为核心人员参与国家级重大项目、国家重点研发计划、国家自然科学基金重点项目等多项重大研究课题。 教育背景 2015/09 – 2020/06:清华大学,能源与动力工程系,动力工程及工程热物理专业,工学博士 2019/03 – 2019/09:阿尔伯塔大学,机械工程系,工程管理专业,博士联合培养 2011/09 – 2015/06:清华大学,能源与动力工程系,能源动力系统专业,工学学士 工作经历 2023/02至今 北京理工大学,管理与经济学院,预聘副教授(特别研究员) 2020/09 – 2023/02: 清华大学,工业工程系,管理科学与工程专业,博士后 荣誉奖励 中国运筹学会运筹应用奖提名奖(排名第四)(2022) 清华大学“水木学者”计划(2020) 清华大学优秀博士学位论文,入选“清华大学优秀博士学位论文丛书”出版项目(2020) 教育部博士研究生“国家奖学金”(2019) 清华大学综合优秀一等奖学金(2018) 全国设备监测诊断与维护会议优秀论文奖(2018) 清华校友-倪维斗院士奖学励志基金(2017) 清华大学三菱重工奖学金(2016)

研究领域

复杂系统智能运维管理、智慧能源管理、科学机器学习、人工智能与工程管理等

近期论文

查看导师新发文章 (温馨提示:请注意重名现象,建议点开原文通过作者单位确认)

Xie Wenzhen, Han Te*, Pei Zhongyi and Xie Min. A unified out-of-distribution detection framework for trustworthy prognostics and health management in renewable energy systems. Engineering Applications of Artificial Intelligence, Forthcoming. (SCI, JCR1区, 中科院分区表Top 期刊) Yao Jiachi and Han Te*. Data-driven lithium-ion batteries capacity estimation based on deep transfer learning using partial segment of charging/discharging data. Energy, 2023, 271, 127033. (SCI, JCR1区, 中科院分区表Top 期刊) Meng Huixing, Geng Mengyao and Han Te*. Long short-term memory network with Bayesian optimization for health prognostics of lithium-ion batteries based on partial incremental capacity analysis. Reliability Engineering & System Safety, 2023, 236, 109288. (SCI, JCR1区, 中科院分区表Top 期刊) Han Te and Li Yan-Fu*. Out-of-distribution detection-assisted trustworthy machinery fault diagnosis approach with uncertainty-aware deep ensembles. Reliability Engineering & System Safety, 2022, 226, 108648. (SCI, JCR1区, 中科院分区表Top 期刊, Top 1% ESI高被引论文) Zhou Taotao, Han Te* and Enrique Lopez Droguett. Towards trustworthy machine fault diagnosis: A probabilistic Bayesian deep learning framework. Reliability Engineering & System Safety, 2022, 224: 108525. (SCI, JCR1区, 中科院分区表Top 期刊, Top 0.1% ESI热点论文,Top 1% ESI高被引论文) Han Te, Wang Zhe* and Meng Huixing. End-to-end capacity estimation of Lithium-ion batteries with an enhanced long short-term memory network considering domain adaptation. Journal of Power Sources, 2022, 520: 230823. (SCI, JCR1区, 中科院分区表Top 期刊) Han Te, Li Yan-Fu* and Qian Min. A hybrid generalization network for intelligent fault diagnosis of rotating machinery under unseen working conditions. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 3520011.( SCI, JCR1区, Top 1% ESI高被引论文) Han Te, Liu Chao*, Wu Rui and Jiang Dongxiang. Deep transfer learning with limited data for machinery fault diagnosis. Applied Soft Computing, 2021, 103: 107150. (SCI, JCR1区, 中科院分区表Top 期刊) Han Te, Liu Chao*, Yang Wenguang and Jiang Dongxiang. Deep transfer network with joint distribution adaptation: a new intelligent fault diagnosis framework for industry application. ISA Transactions, 2020, 97: 269-281. (SCI, JCR1区, 中科院分区表Top 期刊, Top 0.1% ESI热点论文,Top 1% ESI高被引论文) Han Te, Liu Chao*, Yang Wenguang and Jiang Dongxiang. A novel adversarial learning framework in deep convolutional neural network for intelligent diagnosis of mechanical faults. Knowledge-Based Systems, 2019, 165: 474-487. (SCI, JCR1区, 中科院分区表Top 期刊, Top 1% ESI高被引论文) Han Te, Liu Chao*, Wu Linjiang, Sarkar Soumik and Jiang Dongxiang. An adaptive spatiotemporal feature learning approach for fault diagnosis in complex systems. Mechanical Systems and Signal Processing, 2019, 117: 170-187. (SCI, JCR1区, 中科院分区表Top 期刊, Top 1% ESI高被引论文) Han Te, Liu Chao*, Yang Wenguang and Jiang Dongxiang. Learning transferable features in deep convolutional neural networks for diagnosing unseen machine conditions. ISA Transactions, 2019, 93: 341-353. (SCI, JCR1区, 中科院分区表Top 期刊) Han Te, Jiang Dongxiang*, Sun Yankui, Wang Nanfei and Yang Yizhou. Intelligent fault diagnosis method for rotating machinery via dictionary learning and sparse representation-based classification. Measurement, 2018, 118: 181-193. (SCI, JCR1区) Han Te*, Jiang Dongxiang, Zhao Qi, Wang Lei and Yin Kai. Comparison of random forest, artificial neural networks and support vector machine for intelligent diagnosis of rotating machinery. Transactions of the Institute of Measurement and Control, 2018, 40(8): 2681-2693. (SCI, JCR3区, Top 1% ESI高被引论文) 韩特, 李彦夫*, 雷亚国, 李乃鹏, 李响. 融合图标签传播和判别特征增强的工业机器人关键部件半监督故障诊断方法. 机械工程学报, 2022, 58(17): 116-124.

学术兼职

《Journal of Risk and Reliability》 (SCI, JCR Q2, FMS B类) Guest Editor, Special Issue: Domain-Knowledge Guided Machine Learning in Safety-Critical Applications 《Measurement Science and Technology》 (SCI, JCR Q1) Guest Editor, Special Issue: AI-Enabled Industrial Equipment Monitoring, Diagnosis and Health Management 《Machines》 (SCI, JCR Q2) Guest Editor, Special Issue: Fault Diagnosis and Health Management of Power Machinery 《Journal of Dynamics, Monitoring and Diagnostics》青年编委 《Frontiers in Mechanical Engineering》编委 IEEE系列《IEEE Transactions on Cybernetics》、《IEEE Transactions on Industrial Electronics》、《IEEE Transactions on Reliability》、《IEEE/ASME Transactions on Mechatronics》,Elsevier系列《Knowledge-Based Systems》、《Advanced Engineering Informatics》、《Applied Soft Computing》等50余种国际期刊同行评审专家 全国自动化系统与集成标准化技术委员会锂电池智能制造装备标准化工作组组员(SAC/TC159/WG18) 中国系统工程学会系统可靠性工程专委会委员 中国机械工程学会设备智能运维分会青年委员 中国可再生能源学会青年工作委员会会员

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