个人简介
教育背景
2010年-2015年 清华大学自动化系，获工学博士学位
2013年-2014年 美国麻省理工学院(MIT)，国家留学基金委联合培养项目
2006年-2010年 浙江大学控制科学与工程系，获工学学士学位
工作履历
2023年-至今 清华大学自动化系，副教授，博士生导师
2020年-2023年 清华大学自动化系，助理教授，博士生导师
2016年-2020年 美国麻省理工学院(MIT)，博士后
学术兼职
TC member, IFAC Technical Committee on Chemical Process Control
TC member, IEEE IES Technical Committee on Data-Driven Control and Monitoring
TC member, IEEE CSS Technical Committee on Process Control
Guest Editors, Machines; Frontiers in Chemical Engineering; Results in Control and Optimization
Science Advances, Joule, Automatica, IEEE TCST, IEEE TASE, IEEE TII, IEEE CDC, ACC, IFAC World Congress等国际期刊和会议审稿人
奖励与荣誉
Intelligent Computing Innovators of China, DeepTech, 2022
Outstanding Reviewer for Journal of Process Control, 2018
瑞士乔诺法(Chorafas)青年研究奖, 2016
北京市优秀毕业生, 2015
清华大学优秀博士论文, 2015
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）
主要期刊论文
Benben Jiang, William E. Gent, Fabian Mohr, Supratim Das, Marc D. Berliner, Michael Forsuelo, Hongbo Zhao, Peter M. Attia, Aditya Grover, Patrick K. Herring, Martin Z. Bazant, Stephen J. Harris, Stefano Ermon, William C. Chueh, Richard D. Braatz. Bayesian learning for rapid prediction of lithium-ion battery cycling protocols. Joule, 2021. (Tsinghua Press Release: www.tsinghua.edu.cn/info/1175/88412.htm) (IF=41.2, Cover Article)
Kristen Severson, Peter Attia, Norman Jin, Nicholas Perkins, Benben Jiang, Zi Yang, Michael H. Chen, Muratahan Aykol, Patrick K. Herring, Dimitrios Fraggedakis, Martin Z. Bazant, Stephen J. Harris, William C. Chueh, Richard D. Braatz. Data-driven prediction of battery cycle life before capacity degradation. Nature Energy, 4: 383–391, 2019. (IF=46.4, Cover Article)
Benben Jiang, Marc Berliner, Kun Lai, Patrick Asinger, Hongbo Zhao, Patrick Herring, Martin Z. Bazant, Richard D. Braatz. Fast charging design for Lithium-ion batteries via Bayesian optimization. Applied Energy, 307, 118244, 2022.
Guijun Ma, Songpei Xu, Benben Jiang, Cheng Cheng, Xin Yang, Yue Shen, Tao Yang, Yunhui Huang, Han Ding, Ye Yuan. Real-time personalized health status prediction of lithium-ion batteries using deep transfer learning. Energy & Environmental Science, 2022
Benben Jiang, Xizhe Wang. Constrained Bayesian optimization for minimum-time charging of Lithium-ion batteries. IEEE Control Systems Letters. 6, 1682–1687, 2022.
Benben Jiang, Lu Qiugang. Fault detection in industrial systems using maximized divergence analysis approach. IEEE Access, 10, 60674–60681, 2022.
Marc D. Berliner, Hongbo Zhao, Supratim Das, Michael Forsuelo, Benben Jiang, William C. Chueh, Martin Z. Bazant, and Richard D. Braatz. Nonlinear identifiability analysis of the porous electrode theory model of lithium-ion batteries. Journal of The Electrochemical Society, 168, 090546, 2021.
Benben Jiang, Bofan Zhu. Dynamic Bhattacharyya bound-based approach for fault classification in industrial Processes. IEEE Transactions on Industrial Informatics, 18, 397–404, 2021.
Qiugang Lu, Benben Jiang*, Eranda Harinath. Fault diagnosis in industrial processes by maximizing pairwise Kullback-Leibler divergence. IEEE Transactions on Control Systems Technology, 29, 780–785, 2019.
Benben Jiang, Yi Luo, Qiugang Lu. Maximized mutual information analysis based on stochastic representation for process monitoring. IEEE Transactions on Industrial Informatics, 15, 1579–1587, 2019.
Benben Jiang, Zifeng Guo, Qunxiong Zhu, Gao Huang. Dynamic minimax probability machine-based approach for fault diagnosis using pairwise discriminate analysis. IEEE Transactions on Control Systems Technology, 27, 806–813, 2019.
Qiugang Lu, Benben Jiang*, R. Bhushan Gopalunia, Philip D. Loewend, Richard D. Braatz. Sparse canonical variate analysis approach for process monitoring. Journal of Process Control, 71, 90–102, 2018.
Qiugang Lu, Benben Jiang, R. Bhushan Gopalunia, Philip D. Loewend, Richard D. Braatz. Locality preserving discriminative canonical variate analysis for fault diagnosis. Computers & Chemical Engineering, 17, 309–319, 2018.
Benben Jiang, Richard D. Braatz. Fault detection of process correlation structure using canonical variate analysis-based correlation features. Journal of Process Control, 58, 131–138, 2017.
Benben Jiang, Xiaoxiang Zhu, Dexian Huang, Joel A. Paulson, Richard D.Braatz. A combined canonical variate analysis and fisher discriminant analysis (CVA-FDA) approach for fault diagnosis. Computers & Chemical Engineering, 77:1–9, 2015.
Benben Jiang, Xiaoxiang Zhu, Dexian Huang, Richard D. Braatz. Canonical variate analysis-based monitoring of process correlation structure using causal feature representation. Journal of Process Control, 32, 109–116, 2015.
Leo H. Chiang, Benben Jiang, Xiaoxiang Zhu, Dexian Huang, Richard D. Braatz. Diagnosis of multiple and unknown faults using the causal map and multivariate statistics. Journal of Process Control, 28, 27–39, 2015.
Benben Jiang, Fan Yang, Wei Wang, Dexian Huang. Simultaneous identification of bi-directional path models based on process data. IEEE Transactions on Automation Science and Engineering, 12, 666–679, 2015.
Benben Jiang, Dexian Huang, Xiaoxiang Zhu, Fan Yang, Richard D. Braatz. Canonical variate analysis-based contributions for fault identification. Journal of Process Control, 26, 17–25, 2015.
Benben Jiang, Fan Yang, Wei Wang, Dexian Huang. Simultaneous identification of bi-directional paths in closed-loop systems with colored noise. Automatica, 58, 139–142, 2015.
主要会议论文
Benben Jiang, Weike Sun, Richard D. Braatz. An information-theoretic framework for fault detection evaluation and design of optimal dimensionality reduction methods. IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, Poland, Aug. 2018: 1311–1316.
Weike Sun, Benben Jiang, Richard D. Braatz. Concurrent canonical variate analysis for process operating condition deviations and dynamic anomalies monitoring. AIChE Annual Meeting, Pittsburgh?, USA, Aug. 2018. (Finalist for the CAST Directors Best Student Presentation Award)
Benben Jiang, Zifeng Guo, Gao Huang. Pairwise discriminate analysis based minimax probability machine approach for fault diagnosis. IEEE Conference on Control Technology and Applications, Hawaii, USA, Aug. 2017: 1486–1491.
Benben Jiang, Qunxiong Zhu, Xiaoxiang Zhu. A generalized instrumental variable method based on matrix decomposition for simultaneous identification of bi-directional paths in closed-loop systems. IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, Norway, June 2016: 1115–1120.
Benben Jiang, Fan Yang, Dexian Huang, Wei Wang. Extended-AUDI method for simultaneous determination of causality and models from process data. American Control Conference, Washington, USA, June 2013: 2491–2496.
Benben Jiang, Fan Yang, Yongheng Jiang, Dexian Huang. An extended AUDI algorithm for simultaneous identification of forward and feedback paths in closed-loop systems. IFAC Symposium on Advanced Control of Chemical Processes, Singapore, July 2012:396–401.
(*通讯作者)
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