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1、2017英语自我介绍演讲稿_2017英语自我介绍演讲稿以下是本人精心为您编辑整理的英语自我介绍演讲稿，供您参考，我们会持续更新，请留意，更多详细内容请点击我查看。General IntroductionI am a third year master major in automation at Shanghai Jiao Tong University, P. R. China. With tremendous interest in Industrial Engineering, I am writing to apply for acceptance into your Ph.D. gr
2、aduate program.Education backgroundIn 1995, I entered the Nanjing University of Science Technology (NUST) - widely considered one of the China s best engineering schools. During the following undergraduatestudy, my academic records kept distinguished among the whole department. I was granted First C
3、lass Prize every semester,In 1999, I got the privilege to enter the graduate program waived of the admission test.At the period of my graduatestudy, my overall GPA(3.77/4.0) ranked top 5% in the department. In the second semester, I became teacher assistant that is given to talented and matured stud
4、ents only. This year, I won the Acer Scholarship as the one and only candidate in my department, which is the ultimate accolade for distinguished students endowed by my university. Presently, I am preparing my graduation thesis and trying for the honor of Excellent Graduation Thesis.Research experie
5、nce and academic activityWhen a sophomore, I joined the Association of AI Enthusiast and began to narrow down my interest for my future research. With the tool of OpenGL and Matlab, I designed a simulation program for transportation scheduling system. It is now widely used by different research grou
6、ps in NUST. I assumed and fulfilled a sewage analysis dispose project for Nanjing sewage treatment plant. This was my first practice to convert a laboratory idea to a mercial product.In retrospect, I find myself standing on a solid basis in both theory and experience, which has prepared me for the Ph.D. program. My future research interests include: Network Scheduling Problem, Heuristic Algorithm research (especially in GA and Neural network), Supply chain network research, Hybrid system performance analysis with Petri nets and Data Mining.
