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大学开学自我介绍范文:新生版(英文)

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发表于 2016-7-11 08:55:01 | 显示全部楼层 |阅读模式
  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.
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