应届生面试的英语自我介绍范文

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2021年01月23日 17:16
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2021年1月23日发(作者:弄璋是指生了)

应届生面试的英语自我介绍范文



I am from Guangxi University for Nationalities
professional graduates. Allow me to take up a few
minutes examiners to conduct a self- introduction!


After several years of university campus life, I
learned a lot of knowledge. I am pleased to accept and
learn new things and do things in life are so self-
disciplined; students do in the Director- General, through
a wide range of unusual and effective improvement
measures to complete the Communication and cooperation
between the departments. A serious and responsible work.
With team spirit. Academic performance among the best in
class, studying and strong interest in learning the
spirit of the regular teachers have been well received.


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, and my overall
GPA(89.5/100) ranked No.1 among 113 students. In 1999, I
got the privilege to enter the graduate program waived of
the admission test. I selected the Shanghai Jiao Tong
University to continue my study for its best reputation
on Combinatorial Optimization and Network Scheduling
where my research interest lies.


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. In 1997, I participated in simulation
tool development for the scheduling system in Prof.
Wang’s lab. 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. In 1998, 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 1999, I joined the distinguished Professor Yu-
Geng Xis research group aiming at Network flow problem
solving and Heuristic algorithm research. Soon I was
engaged in the FuDan Gene Database Design. My duty was to
pick up the useful information among different kinds of
gene matching format. Through the comparison and analysis
for many heuristic algorithms, I introduced an improved
evolutionary algorithm -- Multi-population Genetic
Algorithm. By dividing a whole population into several
sub- populations, this improved algorithm can effectively
prevent GA from local convergence and promote various
evolutionary orientations. It proved more efficiently
than SGA in experiments, too. In the second semester, I
joined the workshop-scheduling research in Shanghai Heavy
Duty Tyre plant. The scheduling was designed for the
rubber-making process that covered not only discrete but
also continuous circumstances. To make a balance point
between optimization quality and time cost, I proposed a
Dynamic Layered Scheduling method based on hybrid Petri
Nets. The practical application showed that the average
makespan was shortened by a large scale. I also
publicized two papers in core journals with this idea.
Recently, I am doing research in the Composite Predict of
the Electrical Power system assisted with the technology
of Data Mining for Bao Steel. I try to combine the
Decision Tree with Receding Optimization to provide a new

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