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自我介绍演讲稿英文版

更新时间:2023-08-09 17:03:22 来源:高考在线

自我介绍演讲稿英文版

  General Introduction

  I 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。 graduate program。

  Education background

  In 1995, I entered the Nanjing University of Science & Technology (NUST) -- widely considered one of the China’s best engineering schools。 During the following undergraduate study, my academic records kept distinguished among the whole department。 I was granted First Class Prize every semester,In 1999, I got the privilege to enter the graduate program waived of the admission test。

  At the period of my graduate study, 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 students 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 experience and academic activity

  When 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 groups 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 commercial 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。