韓特
韓特，現就職于偉德國際1946bv官網/能源與環境政策研究中心，預聘副教授、特別研究員、博士生導師，碳中和系統工程北京實驗室主任助理。入選中國科協“青年人才托舉”，清華大學“水木學者”，斯坦福全球前2%頂尖科學家（2021-2024連續4年），曾獲清華大學優秀博士學位論文、中國運籌學會運籌應用獎等榮譽。
主要研究方向包括智慧能源管理、信息能源系統、AI驅動的工業故障預測與健康管理、科學機器學習等。以第一/通訊作者身份在國際頂級SCI期刊上發表論文20余篇，入選ESI前1%高被引論文10余篇，ESI前0.1%熱點論文5篇，授權國家發明專利10余項。擔任人工智能領域頂級SCI期刊Applied Soft Computing編委、SCI期刊IEEE Sensors Journal副編輯，SCI期刊Reliability Engineering & System Safety、IEEE Transactions on Industrial Cyber-Physical Systems等國際著名期刊客座編輯。主持國家自然科學基金、北京市自然科學基金、中國博士后科學基金特別資助等國家級/省部級縱向項目課題9項，作為核心人員參與多項國家級重大/重點項目。
招生學科：管理科學與工程
歡迎對智慧能源管理、機器學習、AI大模型等方向感興趣的同學聯系攻讀碩士、博士研究生。
聯系方式
地址：北京市海淀區中關村南大街5號偉德國際1946bv官網（100081）
Email：hante@bit.edu.cn, hant15@tsinghua.org.cn
教育背景
2011/09 – 2015/06：清華大學，能源與動力工程系，工學學士
2015/09 – 2020/06：清華大學，能源與動力工程系，工學博士
2019/03 – 2019/09：阿爾伯塔大學，機械工程系，博士聯合培養
工作經歷
2020/09 – 2023/02：清華大學，工業工程系，博士后
2023/02至今 偉德國際1946bv官網，偉德國際1946bv官網/能源與環境政策研究中心，預聘副教授、博士生導師
2024/05至今 偉德國際1946bv官網，碳中和系統工程北京實驗室，主任助理
代表性論文（*通訊作者, #共同第一作者）
[1] Chang Zhonghao, Han Te*. Prognostics and health management of photovoltaic systems based on deep learning: A state-of-the-art review and future perspectives. Renewable and Sustainable Energy Reviews, 2024, 205, 114861. (SCI, JCR1區, 中科院Top期刊)
[2] Chang Zhonghao, Jia Kaiwen, Han Te*, Wei Yi-Ming. Towards more reliable photovoltaic energy conversion systems: A weakly-supervised learning perspective on anomaly detection. Energy Conversion and Management, 2024, 316, 118845. (SCI, JCR1區, 中科院Top期刊)
[3] Han Te, Cong Rong-Gang*, Yu Biying, Tang Baojun, Wei Yi-Ming*. Integrating local knowledge with ChatGPT-like large-scale language models for enhanced societal comprehension of carbon neutrality. Energy and AI, 2024, 18, 100440.
[4] Han Te, Tian Jinpeng*, Chung C. Y.*, Wei Yi-Ming. Challenges and opportunities for battery health estimation: Bridging laboratory research and real-world applications. Journal of Energy Chemistry, 2024, 89, 434-436. (SCI, JCR1區, 中科院Top期刊)
[5] Yao Yuantao, Han Te*, Yu Jie, Xie Min. Uncertainty-aware deep learning for reliable health monitoring in safety-critical energy systems. Energy, 2024, 291, 130419. (SCI, JCR1區, 中科院Top期刊, Top 1% ESI高被引論文)
[6] Yao Jiachi, Chang Zhonghao, Han Te*, Tian Jinpeng*. Semi-supervised adversarial deep learning for capacity estimation of battery energy storage systems. Energy, 2024, 294, 130882. (SCI, JCR1區, 中科院Top期刊, Top 1% ESI高被引論文)
[7] Chan Joey*#, Han Te#, Pan Ershun. Variational autoencoder-driven adversarial SVDD for power battery anomaly detection on real industrial data. Journal of Energy Storage, 2024, 103, Part B, 114267. (SCI, JCR1區, 中科院Top期刊)
[8] Cheng Yongbo, Qv Junheng, Feng Ke, Han Te*. A Bayesian adversarial probsparse Transformer model for long-term remaining useful life prediction. Reliability Engineering & System Safety, 2024, 248, 110188. (SCI, JCR1區, 中科院Top期刊)
[9] Chang Zhonghao, Zhang An-jun, Wang Huan*, Xu Jiajia, Han Te*. Photovoltaic cell anomaly detection enabled by scale distribution alignment learning and multi-scale linear attention framework. IEEE Internet of Things Journal, 2024, 11(16): 27816-27827. (SCI, JCR1區, 中科院Top期刊)
[10] Zhang Xiaochen, Wang Chen, Zhou Wei, Xu Jiajia, Han Te*. Trustworthy diagnostics with out-of-distribution detection: A novel max-consistency and min-similarity guided deep ensembles for uncertainty estimation. IEEE Internet of Things Journal, 2024, 11(13): 23055-23067. (SCI, JCR1區, 中科院Top期刊)
[11] Liu Ruonan, Zhang Quanhu, Han Te*, Yang Boyuan*, Zhang Weidong, Yin Shen and Zhou Donghua. Survey on foundation models for prognostics and health management in industrial cyber-physical systems. IEEE Transactions on Industrial Cyber-Physical Systems, 2024, 2: 264-280.
[12] 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區, 中科院Top期刊, Top 0.1% ESI熱點論文, Top 1% ESI高被引論文)
[13] Han Te, Xie Wenzhen*, Pei Zhongyi. Semi-supervised adversarial discriminative learning approach for intelligent fault diagnosis of wind turbine. Information Sciences, 2023, 648, 119496. (SCI, JCR1區, 中科院Top期刊, Top 0.1% ESI熱點論文, Top 1% ESI高被引論文)
[14] 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, 2023, 125, 106707. (SCI, JCR1區, 中科院Top期刊)
[15] Wang Zhe, Wu Zhiying, Li Xingqiu, Shao Haidong, Han Te*, Xie Min. Attention-aware temporal-spatial graph neural network with multi-sensor information fusion for fault diagnosis. Knowledge-Based Systems, 2023, 278, 110891. (SCI, JCR1區, 中科院Top期刊)
[16] Miao Yonghao, Li Chenhui, Shi Huifang and Han Te*. Deep network-based maximum correlated kurtosis deconvolution: A novel deep deconvolution for bearing fault diagnosis. Mechanical Systems and Signal Processing, 2023, 189: 110110. (SCI, JCR1區, 中科院Top期刊, Top 1% ESI高被引論文)
[17] 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區, 中科院Top期刊, Top 0.1% ESI熱點論文, Top 1% ESI高被引論文)
[18] 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區, 中科院Top期刊, Top 0.1% ESI熱點論文, Top 1% ESI高被引論文)
[19] 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區, 中科院Top期刊, Top 0.1% ESI熱點論文, Top 1% ESI高被引論文)
[20] 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區, 中科院Top期刊)
[21] 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區, 中科院Top期刊, Top 1% ESI高被引論文)
[22] 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區, 中科院Top期刊, Top 1% ESI高被引論文)
[23] 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區, 中科院Top期刊, Top 0.1% ESI熱點論文，Top 1% ESI高被引論文)
[24] 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區, 中科院Top期刊, Top 1% ESI高被引論文)
[25] 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區, 中科院Top期刊, Top 1% ESI高被引論文)
[26] 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區, 中科院Top期刊)
[27] 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區, 中科院Top期刊)
[28] 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區, Top 1% ESI高被引論文)
[29] 韓特, 李彥夫*, 雷亞國, 李乃鵬, 李響. 融合圖標簽傳播和判別特征增強的工業機器人關鍵部件半監督故障診斷方法. 機械工程學報, 2022, 58(17): 116-124.
科研項目
[1] 中國科協“青年人才托舉工程”項目：“可解釋、可通用”科學機器學習賦能的復雜系統智能運維，2023/12-2025/12，負責人
[2] 國家自然科學基金青年基金項目：小樣本下風力發電機系統運行健康狀態表征與域泛化智能診斷研究，2023/01-2025/12，負責人
[3] 北京市自然科學基金豐臺前沿項目：機理-數據聯合驅動的鐵路物流園區智慧能源管控方法研究，2024/10-2027/09，負責人
[4] 工業與信息化部指導性軟課題：面向新型工業化的企業節能降碳優化控制與數字化碳管理研究，2024/05-2024/12，負責人
[5] 安徽省科技創新攻堅計劃項目：水泥窯余熱低碳梯級綠色高效利用關鍵技術研究及應用，2024/09-2027/09，課題負責人
[6] 寧夏回族自治區重點研發專項：電化學液冷儲能系統健康診斷與安全保障技術研究，2024/06-2027/05，課題負責人
[7] 安徽省科技重大專項“揭榜掛帥”項目：面向工業互聯網的多模態智能感知與認知決策技術攻關，2023/05-2025/12，子課題負責人
[8] 中國博士后科學基金特別資助、面上資助：數據驅動的高速列車傳動系統智能故障診斷與根原因分析方法研究，2021/05-2022/09，負責人
[9] 企業橫向委托-中國船舶集團系統工程研究院：機電設備亞健康狀態識別技術輔助研究及功能演示，2023/06-2024/06，負責人
學術兼職與服務
Editor of Applied Soft Computing, 2024-. (SCI, JCR Q1, 中科院一區Top期刊)
Associate Editor of IEEE Sensors Journal, 2023- (SCI, JCR Q1, 中科院二區期刊)
《能源與氣候變化》編委
《綜合智慧能源》青年編委
Leading Guest Editor of Reliability Engineering & System Safety (SCI, JCR Q1, 中科院一區Top期刊, FMS B類), Special Issue: Scientific Machine Learning for Enhancing Reliability and Safety of AI-powered Systems
Guest Editor of Journal of Risk and Reliability (SCI, JCR Q2, FMS B類), Special Issue: Domain-Knowledge Guided Machine Learning in Safety-Critical Applications
Guest Editor of IEEE Transactions on Industrial Cyber-Physical Systems, Special Issue: Machine Learning for Prognostics and Health Management of Industrial Cyber-physical Systems
Guest Editor of Measurement Science and Technology (SCI, JCR Q1, 中國科協高質量科技期刊分級目錄T1級期刊), Special Issue: AI-Enabled Industrial Equipment Monitoring, Diagnosis and Health Management
北京市運籌學會副秘書長
中國“雙法”研究會能源經濟與管理研究分會理事
中國機械工程學會工業大數據與智能系統分會委員
中國系統工程學會系統可靠性工程專業委員會委員
全國自動化系統與集成標準化技術委員會鋰電池智能制造裝備標準化工作組組員(SAC/TC159/WG18)
多個國際會議組委會成員或分論壇主席: IEEE Global Reliability & Prognostics and Health Management Conference (2023, 2024), International Conference on Artificial Intelligence and Autonomous Transportation (2024), International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (2022, 2023), etc.
主要榮譽獎勵
● 中國發明協會“發明創業獎”（二等獎，2/10）（2024）
● 斯坦福全球前2%頂尖科學家（2024）
● 中國科協“青年人才托舉工程”（2023）
● 斯坦福全球前2%頂尖科學家（2023）
● 中國運籌學會“運籌應用獎”（提名獎，4/12）（2022）
● 斯坦福全球前2%頂尖科學家（2022）
● 斯坦福全球前2%頂尖科學家（2021）
● 清華大學優秀博士學位論文，入選“清華大學優秀博士學位論文叢書”出版項目（2020）
● 清華大學“水木學者”（2020）
● 教育部博士研究生“國家獎學金”（2019）
教學課程
《機器學習》（全英文）本科生課程
《碳市場實踐》研究生課程
學生培養
● 指導本科生韓明陽、駱道平等獲第十九屆“挑戰杯”全國大學生課外學術科技作品競賽2024年度“揭榜掛帥”專項賽特等獎
● 指導本科畢設學生常中豪獲批2024年北京市自然科學基金本科生“啟研”計劃
● 指導本科畢設學生常中豪獲清華大學直博生推免資格
