Alumnus Zhang Zheng Got the Outstanding PhD Dissertation Award in EDA
Recently, Association for Computing Machinery (ACM) has announced on its official website the result of Outstanding PhD Dissertation Award selection. Dr. Zhang Zheng from MIT, the Alumnus of School of Optical and Electronic Information in Huazhong University of Science and Technology (HUST), has won the ACM Outstanding PhD Dissertation Award in Electronic Design Automation in 2006 with his dissertation “Uncertainty Quantification for Integrated Circuits and Microelectromechanical Systems”.
The award, as the top one in EDA, accepts nominations from deans of any university worldwide. However, only one of the at most two PhD dissertations from each university will enter the final assessment stage. This year, awarding ceremony will be held during Design Automation Conference in Austin of Texas, US in June.
Zhang Zheng was admitted in School of Optical and Electronic Information in HUST as an undergraduate student in 2004.
In 2008, he went to Hongkong University for MPhil degree in Electrical and Electronic Engineering with a full scholarship . During this period, he got 2011 Li Ka Shing Prize (best MPhil/PhD thesis award from the University of Hong Kong).
In 2010, Zhang Zheng entered Department of Electrical Engineering and Computer Science in MIT for doctorate again with the full scholarship. During his doctoral study, He as the lead author won 2014 Donald O. Pederson Best Paper Award from IEEE Transactions on CAD of Integrated Circuits and Systems (the top journal in EDA) as well as 2014 Chinese Government Award for Outstanding Students Abroad.
In 2015, he received MIT Microsystems Technology Laboratory (MTL) Doctoral Dissertation Seminar Award, which is the only award of MTL for PhD dissertations.
Zhang Zheng’s main research interest is high-dimensional uncertainty quantification and data analysis, the primary application of which is stochastic modeling and simulation of integrated circuits, microelectromechanical systems and silicon photonics that are influenced by significant Nano-scale manufacturing process variations. The recent engineering applications also include analysis of Uncertainty Quantification for power systems and problems about electromagnetic calculation in MRI and high-dimensional data processing.