《英语自我介绍演讲稿优秀演讲稿.doc》由会员分享，可在线阅读，更多相关《英语自我介绍演讲稿优秀演讲稿.doc（3页珍藏版）》请在金锄头文库上搜索。
1、英语自我介绍演讲稿优秀演讲稿为大家收集整理了英语自我介绍演讲稿优秀演讲稿供大家参考，希望对大家有所帮助！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 yourgraduate program.Education backgroundI
2、n 1995, I entered the Nanjing University of Science & Technology (NUST) - widely considered one of the Chinas 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,
3、 I got the privilege to enter the graduate program waived of the admission test.At the period of my graduate study, my overall GPA(/) 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 Sch
4、olarship 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 activityWhen a sophomor
5、e, 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 se
6、wage 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 theprogram. 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.
