Chun-Chieh Wang

Hi, I am Philip.
I am a strong self-motivating active learner, always full of curiosity about many things, and cross-domain integration is one of my proudest strengths.
Recommendation algorithm is my current research field, mainly focusing on Graph-based Recommendation systems.
Since the E-commerce and Streaming media services are booming in these years, I believe that we would be heavily relying on productive cloud services and good recommendation systems for targeting audiences and customers efficiently. I hope I could contribute to the innovation of web service applications in my future career.


Education

National Chengchi University

CLIP Lab [link], Master degree
Major: Computer Science

Research Topic: Graph-based recommendation relevant

Sep 2019 - expected Jun 2021

National Taipei University

Bachelor degree
Major: Computer Science and Information Engineering

Research Topic: Improving the Trading Strategy via Reinforcement Learning

Sep 2015 - Jun 2019

Taipei Municipal Jianguo High School

math and science concentration

Sep 2012 - Jun 2015

Experience

Part-time Research & Development

KKBOX, NCCU CLIP Research Team [link]

Research on recommendation algorithms based on user-item interaction graphs.

Jan 2020 – Jun 2020

Part-time Engineer

National Taiwan University, Digital Finance and Industry Development Centre [link]

Assist in the development of financial engineering algorithms related to machine learning and deep learning.

Aug 2018 - Jun 2019

Part-time Research Assistance

Ti-Ching Peng, Associate Professor [link]

Assist in analysis of the real estate data and help to implement the machine learning methods for further research topics.

Sep 2017 - present

Part-time Engineer

China Trust Commercial Bank, Foreign Exchange Department [link]

Research on deep learning applied to trading algorithms, and also use text mining skills to analyze social media discussions, forex news and financial reports.

Mar 2017 - Mar 2018

DEMO

All project source codes can be found in my GITHUB

RLFXer

MOST research project: Improving Foreign Exchange Trading Strategies via Reinforcement Learning

Result
NTPU Rate

A demo that shows some analytic results from social media (currently Facebook).

Source
MAFXer

This is a tutorial of how to trade forex with "Moving Average (MA)" smartly.

Powerpoint
Korean Fish Chatbot

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SourceDemo
FX-Peeker

Inspired from CTBC forex trading team. The website provides "Candlestick Pattern Matching" and "Sentiment Analyze" service for forex trading.

Paper
Multi-layer Percpetron .JS

A demo website that implemented Multi-layer Perceptron (MLP) in pure native JavaScript.

Website
Kohonen Network .JS

A demo website that implemented Kohonen Network in pure native JavaScript.

Website
Hopfield Neural Network .JS

A demo website that implemented Hopfield Neural Network in pure native JavaScript

Source
NTPU allStar League

A demo version website of the voting system for 2017 NTPU Allstar League.

Website

ACHIEVEMENTS

Publications
Conferences
  • Deep Reinforcement Learning for Foreign Exchange Trading
    Chun-Chieh Wang & Yun-Cheng Tsai
    The 33th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2020)

  • The application of big data on house prices in Japan: Web data mining and machine learning
    Ti-Ching Peng*, Chun-Chieh Wang
    Annual International Conference on Recent Advances in Business, Economics, Social Sciences and Humanities (RBESH), Tokyo, 2018/10

  • An Efficiency Comparison on Chinese Typewriting between Zhuyin Pinyin and Hanyu Pinyin
    Chun-Chieh Wang
    International Conference of Innovation and Design (ICID) 2013

Working Papers
M.O.S.T. Research Projects
  • Topic: 透過深度增強學習開發交易輔助優化系統
    Project No.: 107-2813-C-002-088-E
    Timeline: 2018/07/01 - 2019/02/28
Awards