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Chen Liang Yun

Expertise: Machine Learning, Data Analysis, Algorithm Design Personality: Efficient, Focused, Cooperative, Patient. 


I've already performed my military service.

 I am a recent graduate of Cheng Kung University's Department of Geomatics, and I expect to graduate in August 2020. I am familiar with Python, Java, C, and other languages. I am interested in data analysis and enjoy organizing and maintaining data from different sources. When I find trends and correlations in different data and apply these patterns to problems will give me a strong sense of accomplishment. Enjoys learning new technologies, understanding algorithms quickly, and continually refining skills.


Education

Master of Engineering in Geomatics, National Cheng Kung University, Tainan, Taiwan

Bachelor of Computer Science, Feng Chia University, Taichung, Taiwan

Master Thesis


Skyline Query for Multi-Request Route Planning with Time Constraint

  • we address a new problem called Multi-Request Route Planning with Time Constraint
  • we design an algorithm to find optimal solution in unlimited time and approximate solution in limited time 

Bachelor's Independent Study


Motion Recognition System (JARVISH) based on triaxial accelerometer signals mounted on the helmet.

  • Collects triaxial accelerometer data from the helmet, pre-processes the data, and identifies the rider's head movements during the ride using neural network.

Working Experience

National Cheng Kung University, Project Research Assistant, Ministry of Science and Technology, Jun 2019 ~ Jan 2020

GIS WEB design

National Cheng Kung University, Project Research Assistant, Ministry of Science and Technology, Jun 2019 ~ Jan 2020

Escape route planning

Skills


Python

Pandas、NumPy、scikit-learn、TensorFlow 、pytorch、requests、opencv、Matplotlib、Beautiful Soup


Other Programming language

C、C++、Java、SQL、R


DataBase

MySQL


Version Control

git、SourceTree


Other Skills

  • Machine Learning 
  • Neural Network 
  • Decision Support Systems 
  • Algorithm Design 
  • Web Crawler


language skills

English

Mandarin

Git Hub


Crawler 

  • Crawl the price of interesting stocks, visualize the data, and data backtesting based on the strategy.

Mahjong 

  • Generate mahjong pictures for use in object recognition

Course work - Master


  1. Digital image processing - edge detection, using watershed algorithms.
  2. Neural network applications - using K-NN, K-Means, SVM, neural networks to analyze interest data.
  3. Machine Learning - Diabetes classification using Naive-Bayes and Dirichlet distribution.
  4. Database Management System - Flawed coffee bean identification using cycleGAN in combination with VGG16.

Course Work - Bachelor

  1. Programming Practicum - Command Window Baseball game
  2. Database System - Mobile Query System
  3. iOS APP Design - Daily Necessities Billing Calculator
  4. Data Warehousing and Data Mining - Self-study site adhesion analysis, using DNN, Random Forest.

Autobiography


  My name is Liang Yun Chen, and I wanted to be an IT engineer since I was a kid because I thought I could play with computers. I have studied C language in high school, but I didn't realize it was what I thought it would be until I went to college to study Computer Science. My interest in data analysis and data processing deepened during my studies, and I want to become an information technology engineer even more.


I am goal orientated, efficient, highly focused, and observant—ideal for work related to data analysis.


I graduated from Feng Chia University with a degree in Computer Science and completed my Master's degree in the Department of Geomatics at National Cheng Kung University.

   

In college, I built up necessary programming skills and learned Java, C, C++, and Python, R, and database design in my senior year of college, and built up a basic understanding of machine learning and neural network algorithms through Python. I joined the Mining and Applications on Geospatial Information Computing Laboratory to refine the skills in data mining and algorithm design.


During my master's degree, I worked on designing algorithms related to the Internet of Things (IoT) in the lab. I also have a deeper understanding of basic machine learning methods such as K-means, Bayesian classification, decision tree classification, and neural network design methods such as DNN, CNN, RNN, etc. My thesis research topic is related to the skyline query, an algorithm used in multi-decisional systems. I think it can be used in different ways, such as pre-processing data and correlation analysis to filter out useful features.


In the future, I will continue to improve my knowledge of machine learning and deep learning. I am currently working on the Slide Project on image recognition. The main problem is that it is easy to over-fit the test data for deep learning object recognition, especially the influence of the background. It would be a significant breakthrough if we can find a way to generate data that can improve the model's stability.

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