Benben JIANG

Associate Professor

Department of Automation

Beijing University of Chemical Technology

No.15 Beisanhuan East Road, Chaoyang District

Beijing 100029, China

Email: jiangbb@mail.buct.edu.cn

  Education

Ph. D. in Control Science and Engineering, Tsinghua University, Beijing, China, 2015

B.S. in Automation, Zhejiang University, Hangzhou, China, 2010

  Working and Research Experience

Associate Professor, Department of Automation, Beijing University of Chemical Technology, 2015.9 – Present

Visiting Student, Department of Chemical Engineering, Massachusetts Institute of Technology (MIT), 2013.9 – 2014.9

  Research Interests

Process Data Analytics, Information Theory and Statistical Learning, Artificial Intelligence,Fault Detection and Diagnosis, Machine Learning

  Academic Activities

Reviewer of Journal of Process Control, Computers and Chemical Engineering, AIChE Journal, IEEE CDC, IFAC Safeprocess, etc.

   Honors and Awards

Chorafas Foundation Award, The Dimitris N. Chorafas Foundation, Switzerland, 2016

Magna cum laude, Beijing Municipal Education Commission, 2015

Promising Academic Talent, Department of Automation, Tsinghua University, 2015

   Selected Publications

Journal Papers

• B. Jiang, and R. D. Braatz. Fault detection of process correlation structure using canonical variate analysis-based correlation features. Journal of Process Control, 58: 131–138, 2017.

• B. Jiang, Z. Guo, Q. Zhu, and G. Huang. Dynamic minimax probability machine-based approach for fault diagnosis using pairwise discriminate analysis. IEEE Transactions on Control Systems Technology, 2017.

• B. Jiang, X. Zhu, D. Huang, J. A. Paulson, and R. D. Braatz. A combined canonical variate analysis and Fisher discriminant analysis (CVA–FDA) approach for fault diagnosis. Computers and Chemical Engineering, 77:1–9, 2015.

• B. Jiang, F. Yang, W. Wang, and D. Huang. Simultaneous identification of bi-directional paths in closed-loop systems with colored noise. Automatica, 58:139–142, 2015.

• B. Jiang, X. Zhu, D. Huang, and R. D. Braatz. Canonical variate analysis-based monitoring of process correlation structure using causal feature representation. Journal of Process Control, 32:109–116, 2015.

• B. Jiang, D. Huang, X. Zhu, F. Yang, and R. D. Braatz. Canonical variate analysis-based contributions for fault identification. Journal of Process Control, 26:17–25, 2015.

• L. H. Chiang, B. Jiang, X. Zhu, D. Huang, and R. D. Braatz. Diagnosis of multiple and unknown faults using the causal map and multivariate statistics. Journal of Process Control, 28:27–39, 2015.

• B. Jiang, F. Yang, W. Wang, and D. Huang. Simultaneous identification of bi-directional path models based on process data. IEEE Transactions on Automation Science and Engineering, 12: 666–679, 2015.

Conference Papers

• B. Jiang, Q. Zhu, X. Zhu. A generalized instrumental variable method based on matrix decomposition for simultaneous identification of bi-directional paths in closed-loop systems. 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, Norway, June 2016: 1115–1120.

• B. Jiang, F. Yang, D. Huang, and W. Wang. Extended-AUDI method for simultaneous determination of causality and models from process data. 2013 American Control Conference, Washington, June 2013: 2491–2496.

• B. Jiang, F. Yang, Y. Jiang, and D. Huang. An extended AUDI algorithm for simultaneous identification of forward and feedback paths in closed-loop systems. 8th IFAC Symposium on Advanced Control of Chemical Processes, Singapore, July 2012: 396–401..