•Ph.D., Industrial Engineering, the University of South Florida
•B.S., Mechanical Engineering, Shanghai Jiaotong University
•B.S., Business Administration, Shanghai Jiaotong University
Process Monitoring and Diagnosis in Complex Systems;
Statistical Quality Management;
Reliability Test and Analysis.
My research interests mainly address how to exact useful information from the data-rich environments. For example, one of my research goals is to solve engineering problems especially arisen from modern manufacturing processes by using domain knowledge, engineering models and statistical methods. Other application domains I am exploring include semiconductor manufacturing, nanomanufacturing, pharmaceutical engineering and healthcare delivery.
Our research group is engaged in developing advanced technologies to establish a bridge between scientific truth and high-dimensional-and-volume data from complex systems. Recently much of our work has focused on in-situ process monitoring and diagnosis for wafer polishing processes. Not limited to this, we have also dipped our toes into some new research pools such as evolutionary dynamics and complex networks.
•Reviewer of International Journal of Modeling, Identification and Control
•Reviewer of Journal of Manufacturing Systems
•Member of INFORMS and IIE
Selected Recent Publications
Xiaoyun Xu, Xi Zhang and Long Wang, 2011, “Simulating Energy Efficient Wireless Sensor Networks Using Cellular Automata”, Proceedings of the Winter Simulation Conference, accepted.
Lili Chen, Xi Zhang* and Xiaoyun Xu, 2011, “Statistical Modeling and Evaluation of the Survival Data from the Discharge of Hospital Intensive Care Unit”, Proceedings of IIE Asian Conference, pp. 207-215.
Zhang, X., Huang, Q., 2010, “Analysis of Interaction Structure among Multiple Functional Process Variables for Process Monitoring in Semiconductor Manufacturing”, IEEE Transactions on Semiconductor Manufacturing, vol. 23 (2), pp.263-272.
Zhang, X., Wang, H., Huang, Q., Kumar, A., and Zhai, J., 2009, “Statistical and Experimental Analysis of Correlated Time-varying Process Variables for Condition Diagnosis in Chemical-Mechanical Planarization”, IEEE Transactions on Semiconductor Manufacturing, vol. 22 (3), pp.512-521.
Wang, H., Zhang, X., Kumar, A., Huang, Q., 2009, “Nonlinear Dynamics Modeling of Correlated Functional Process Variables for Condition Monitoring in Chemical-Mechanical Planarization”, IEEE Transactions on Semiconductor Manufacturing, vol.22, pp. 188-195.