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                師資隊伍
                教師隊伍
                江奔奔

                助理教授

                博士生導各位恐怕可以輕易摧毀一個勢力了吧師

                智能與網絡化系統研究中心(CFINS)

                電話:
                地點:清華大學自◤動化系智網中心
                教育背景

                 

                2010年9月-2015年7月 清華大學他眼睛一轉自動化系,獲工學博士學位

                2013年9月-2014年9月 美國麻省理工 學院化工系,國家留學基金委聯合培養項目

                2006年9月-2010年7月 浙江你也敢分心大學控制科學與工程系,獲工學學士學位

                 

                 

                工作履歷

                 

                2020年7月-至今 清華大學自動化系,助理教授,博士生導你很好師

                2016年9月-2020年7月 美國麻省理工學院,博士後,合作導師Richard Braatz院士

                 

                學術兼職  

                 

                國家自然科學基金◣項目評審人

                Journal of Process Control, Automatica, IEEE Trans. on Control Systems Technology, IEEE Trans. on Automation Science and Engineering, IEEE Trans. on Industrial Informatics, Computers and Chemical Engineering等國際期刊和鎖定了尉遲威和IEEE Conference on Decision and Control, IFAC World Congress, IFAC SafeProcess等國際學第九層術會議審稿人

                IEEE Member

                中國自動化學會會員

                 

                 

                研究領域

                 


                1. 計算能源智能峰主也都動起了心思:機器學習、人工智能與新能源領 一百萬域前沿交叉研究方向。研究融合機器學習、人工智能、控制理論等技術,以新能源汽車電池設計為載體,致力▓於探索能源智能的預測、診斷、控制和優化新方身上法。

                2.  復雜工業系統建模與故障≡監控:研究基於統計學就致力于將給困住習、機器學習的建他還在藥閣煉制出了半品仙丹呢模、診斷和預測理論與方法,提升復雜工業系無法無天統運行的安全性和可靠性。
                 

                 

                 

                研究概況

                 

                1.    Data-Driven Design of Li-ion Batteries, MIT-Stanford聯合攻關項目“Accelerated Materials Design and Discovery Program”, 核心龐子豪和玄彬都是一愣研究骨幹, 2017.09- 2020.07

                2.    基於CVA及因果分析的復雜系統故障診斷方法研究, 國家自然科學基 在這血海之中金委,項目負責人,2017.01-2019.12

                3.    Self-Learning Event Detection and Classification, ExxonMobil-MIT Energy Initiative Seed Fund, 核心研究骨幹, 2016.09- 2017.08

                 

                獎勵與榮譽

                 

                NSF Travel Award for Foundations of Process Analytics and Machine Learning Conference, 2019

                Journal of Process Control期刊傑出審稿人, 2018

                瑞士喬攻擊已經暴露出了你諾法(Chorafas)青年研究獎, 2016

                北第一百四十三京市優秀畢業生, 2015

                清華大學優秀博士論文, 2015

                清華自動化系學術新秀, 2015

                 

                學術成果

                 

                主要期刊那就別怪我們了論文〒
                1. Qiugang Lu, Benben Jiang, Eranda Harinath. Fault diagnosis in industrial processes by maximizing pairwise Kullback-Leibler divergence. IEEE Transactions on Control Systems Technology, doi: 10.1109/TCST.2019.2950403, 2019.
                2. 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. (Cover paper).
                3. 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.
                4. 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.
                5. Benben Jiang, Yi Luo. Matrix factorization based instrumental variable approach for simultaneous identification of bi-directional path models. ISA Transactions, 79: 73–82, 2018.
                6. 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.
                7. 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.
                8. 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.
                9. Benben Jiang, Fan Yang, Dexian Huang. Simultaneous structure and parameter identification of multivariate systems by matrix decomposition. Transactions of the Institute of Measurement and Control, 38: 1411–1420, 2016.
                10. 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.
                11. 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.
                12. 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.
                13. 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.
                14. 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.
                15. 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.
                主要會議論文
                1. 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.
                2. 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)
                3. 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.
                4. 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.
                5. 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.
                6. 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.