hi everyone :)
i am applying to a UNIST scholarship program! so i was aked to write personal statement!
this is just draft but how do you think, is it ok if i`ll continue writing in this way?
Now I want to represent my study plan.
I always remember the excitement when I first saw The Matrix in which a computer hacker learns from mysterious rebels about the true nature of his reality and his destiny in the war must against its controllers. Some nights later, I had a dream about to be a hacker like him. The dream follows my youth until I got the first touch in my own Windows computer when I was 13. Unfortunately, it was disappointed at that time. Because when I learned to play music by Windows Media Player and realize how dramatically difference between what I was expected and how a computer really looks like.
After all the disappointment of the first use, I was attracted by how to program a small user interface application such as a calculator, or a classical Tetris. But to do so I tried to learn a language program by myself. I coded C-Sharp at that time since it is very popular and can be used to build a user interface with their drag-and-drop toolbox. As a newbie, I always failed to run the code while spent a lot of time to figure what lines of code do. After so many time think about dropping it, I finally make an ugly version of a calculator. At the moment of runnable version was completed, besides, enjoy of successful, I was also filled with confidence and determination that my whole life has to stick with computers and code
It is definitely because of embracing such a dream and my passion for mathematics, I immediately chose to study Computer Science (CS). To build a strong background in CS, I had a hard time to try to understand any motivation behind every concept in Probability, Linear Algebra, especially Multivariance Statistic Analysis, and then I was fascinated by the art of mathematics. Through some classes of Image Processing, Computer Vision, I wondered how mathematics was applied to enhance image quality, compress an image by dimension reduction methods and solve many basic tasks such as image classification, segmentation. However, the first simple image processing method was impressed me a lot that gradient could be used to find edges in an image that nobody told me in the math class. After spending 3 years to learn basic computer science, I had a solid understanding of programming and computer science that not only help me to design a better algorithm but also optimize more efficient with respect to time and storage. Moreover, my background of Linear Algebra and Probability is the building box which helps me to learn easier more advanced computer science courses.
I enjoyed the last wonderful year at university by learning Machine Learning to finish my thesis. At that time, because of rasing Deep Learning when there were many research topics published every week. I was impressed by a topic in which a model generates descriptions for a given image, and I finally decided that my thesis would concentrate on replication of the paper and make some significant improvements on the model. In the next 3 months, I took several online deep learning courses on Stanford Online and Coursera which teach by deep learning pioneers. Through these courses, I learn many basic concepts such as Shannon entropy, Kullback-Leibler (KL) divergence, cross-entropy from the perspective of Information Theory, and then I implemented some state of the art models such as VGGNet, AlexNet, LSTM from scratch. This study was overwhelming but the result was worthwhile, I completed my thesis with distinction.
After graduation, I decided to focus on working instead of pursuing a higher degree immediately. This gives me a chance to immerse in industry, besides, practical engineering is worthy in both industry and academic projects. With 3 years of experience as a data scientist, I learned the focus should be on realistic factors such as user's need instead of only achieve new functions and how important of data management and machine learning feedback loop such as metrics should reflect right user experience. Furthermore, I recognized the importance of data engineering to clean a noised dataset from various sources. In industry, I had opportunities to apply machine learning model such as Matrix Factorization in recommender system which serve millions of users and manipulate data on a huge social graph. At the same time, I also saw the importance of a good team when collaborated with my colleagues to exchange ideas and improve solutions
Another experience when I become a trainer at a nonprofit organization where I teach about the fundamental deep learning for many people with various background. Some of these with the biology major, electricity major, or high school background. This not only gave me an opportunity to work with these people but also developed my communication skills, confidence when speaking in front of a crowd of people. I have gone from being afraid of safe zone to being able to speak in a classroom. It also improved my leadership skill as I helped different groups to finish their assignment and diagnosis bugs in their code.
During the years in both academic and industry. It provided me a strong background in CS with practical experience so now I'm looking forward to learning advanced knowledge about Image Processing, Computer Vision, Machine Learning, especially Deep Learning, and other interesting topics which related to biomedical data as I wished to apply it in healthcare to improve public health and reduce cost of diagnosis process
The CS program at Ulsan National Institute of Science and Technology attract me with core subjects of computer science. Especially, High-performance Visual Computing lab will give me opportunities to explore more topics on biomedical data related image processing. I hope I can contribute my effort into your lab, and accumulate my research experiences. Furthermore, I can expose into industry research in your lab, instead of just completely focus on theory. In conclusion, being a member of your lab will help me become a good researcher, and contribute my efforts to a better life.
I appreciate your attention and consideration in reading this statement.
i am applying to a UNIST scholarship program! so i was aked to write personal statement!
this is just draft but how do you think, is it ok if i`ll continue writing in this way?
Now I want to represent my study plan.
UNIST scholarship program application - study plan
I always remember the excitement when I first saw The Matrix in which a computer hacker learns from mysterious rebels about the true nature of his reality and his destiny in the war must against its controllers. Some nights later, I had a dream about to be a hacker like him. The dream follows my youth until I got the first touch in my own Windows computer when I was 13. Unfortunately, it was disappointed at that time. Because when I learned to play music by Windows Media Player and realize how dramatically difference between what I was expected and how a computer really looks like.
After all the disappointment of the first use, I was attracted by how to program a small user interface application such as a calculator, or a classical Tetris. But to do so I tried to learn a language program by myself. I coded C-Sharp at that time since it is very popular and can be used to build a user interface with their drag-and-drop toolbox. As a newbie, I always failed to run the code while spent a lot of time to figure what lines of code do. After so many time think about dropping it, I finally make an ugly version of a calculator. At the moment of runnable version was completed, besides, enjoy of successful, I was also filled with confidence and determination that my whole life has to stick with computers and code
It is definitely because of embracing such a dream and my passion for mathematics, I immediately chose to study Computer Science (CS). To build a strong background in CS, I had a hard time to try to understand any motivation behind every concept in Probability, Linear Algebra, especially Multivariance Statistic Analysis, and then I was fascinated by the art of mathematics. Through some classes of Image Processing, Computer Vision, I wondered how mathematics was applied to enhance image quality, compress an image by dimension reduction methods and solve many basic tasks such as image classification, segmentation. However, the first simple image processing method was impressed me a lot that gradient could be used to find edges in an image that nobody told me in the math class. After spending 3 years to learn basic computer science, I had a solid understanding of programming and computer science that not only help me to design a better algorithm but also optimize more efficient with respect to time and storage. Moreover, my background of Linear Algebra and Probability is the building box which helps me to learn easier more advanced computer science courses.
I enjoyed the last wonderful year at university by learning Machine Learning to finish my thesis. At that time, because of rasing Deep Learning when there were many research topics published every week. I was impressed by a topic in which a model generates descriptions for a given image, and I finally decided that my thesis would concentrate on replication of the paper and make some significant improvements on the model. In the next 3 months, I took several online deep learning courses on Stanford Online and Coursera which teach by deep learning pioneers. Through these courses, I learn many basic concepts such as Shannon entropy, Kullback-Leibler (KL) divergence, cross-entropy from the perspective of Information Theory, and then I implemented some state of the art models such as VGGNet, AlexNet, LSTM from scratch. This study was overwhelming but the result was worthwhile, I completed my thesis with distinction.
After graduation, I decided to focus on working instead of pursuing a higher degree immediately. This gives me a chance to immerse in industry, besides, practical engineering is worthy in both industry and academic projects. With 3 years of experience as a data scientist, I learned the focus should be on realistic factors such as user's need instead of only achieve new functions and how important of data management and machine learning feedback loop such as metrics should reflect right user experience. Furthermore, I recognized the importance of data engineering to clean a noised dataset from various sources. In industry, I had opportunities to apply machine learning model such as Matrix Factorization in recommender system which serve millions of users and manipulate data on a huge social graph. At the same time, I also saw the importance of a good team when collaborated with my colleagues to exchange ideas and improve solutions
Another experience when I become a trainer at a nonprofit organization where I teach about the fundamental deep learning for many people with various background. Some of these with the biology major, electricity major, or high school background. This not only gave me an opportunity to work with these people but also developed my communication skills, confidence when speaking in front of a crowd of people. I have gone from being afraid of safe zone to being able to speak in a classroom. It also improved my leadership skill as I helped different groups to finish their assignment and diagnosis bugs in their code.
During the years in both academic and industry. It provided me a strong background in CS with practical experience so now I'm looking forward to learning advanced knowledge about Image Processing, Computer Vision, Machine Learning, especially Deep Learning, and other interesting topics which related to biomedical data as I wished to apply it in healthcare to improve public health and reduce cost of diagnosis process
The CS program at Ulsan National Institute of Science and Technology attract me with core subjects of computer science. Especially, High-performance Visual Computing lab will give me opportunities to explore more topics on biomedical data related image processing. I hope I can contribute my effort into your lab, and accumulate my research experiences. Furthermore, I can expose into industry research in your lab, instead of just completely focus on theory. In conclusion, being a member of your lab will help me become a good researcher, and contribute my efforts to a better life.
I appreciate your attention and consideration in reading this statement.
