大学生面试的自我介绍
自我介绍要怎样写才能写得更好?应届生简历网为您提供大学生面试的自我介绍 参考,为了让您在求职时能写出更好的求职简历, 为您推荐一份计算机系毕业生简历为写求职个人简历参考模板。应届生在写个人简历时也可看看其它相关的个人简历模板如这份计算机毕业生简历仅为模板参考,为了更详细让招聘单位更了解自己最好附带一份求职信,写个人求职简历时一定要按自己本人的真实情况填写千万不要夸大自己。
大学生面试的自我介绍
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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