Edward Zhang

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  个人资料

Edward Zhang completed his undergraduate degree in mechanical engineering at Shanghai Jiaotong University. After graduation, he matriculated at Georgia Institute of Technology to pursue his doctoral degree. He has 5 years tutoring experience and enjoys providing academic recommendations to university students. He is passionate about helping people achieve their goals and getting admitted to top universities.

  教育背景

  • 2010.09 - 2016.06
        机械工程
    佐治亚理工学院
  • 2005.09 - 2009.06
        机械工程
    上海交通大学

  有问必答

Q : How do you choose the best postgraduate program to apply for? What are some of the factors to consider?

A : At first, I referred to U.S. News Ranking and QS World University Rankings, and then selected some universities based on specialist ranking and comprehensive ranking. However, when I learned more about universities, I came to realize that their ranks don't really matter. It's important to know that a lower ranked university can still be a very good fit for you. You must know clearly what you want, work or academic research? If you want a job upon graduation, you should pay more attention to the location, the alumni network of the programs while deciding which one to apply. If you intend to continue to develop your academic career, you should focus on the research areas which you are interested in, considering which university is the leader in the field or which professor excels in the field. At this point, it won't matter how highly the university is ranked. All in all, you have to know what you want.

Q : Briefly introduce your research interest.

A : I have maintained a longstanding interest in robotics and automatic controls. Under the guidance of Dr. Sadegh, my research work is in the field of robotics and automation. My main research content is the development of a class of adaptive and learning controllers for nonlinear mechanical systems including robotic manipulators. This work aims to enable a robot to learn a repetitive task through practice, much like a human being, and without requiring a precise model. One implication of this research is that implementing this learning controller can significantly improve the performance of industrial robots without significantly increasing their cost or complexity, and has the potential to improve the accuracy, autonomy, and productivity of automated manufacturing systems.

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