Yao Yang, Hong 洪堯煬

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M.S. student, CS dept., NTHU

Now, my research field is CV, such as deblur or super-resolution, etc. I am good at javascript, python, and C++. I graduated from the CS dept., Taipei Tech, also got 1st place. Trying new fields is what I eager to, therefore I don't scare but happy to learn. That's why I have been explored brand-new courses, events, and places.

  Hsinchu City, Taiwan



National Tsing Hua University

Computer Science

2020 - 2022

National Taipei University of Technology

Computer Science and Information Engineering

3.9/4.0 GPA

1st place

2016 - 2020

Work experiences

Summer Intern  •  Mediatek 

Jul 2021 -  2021



Deep learning (NLP、CV)
Web design
Web crawler
Chat bot (Discord)
Desktop program


Microsoft Office
Visual Studio Code
Windows 10 / 7 / Xp
Ubuntu 16.04 / 18.04

Programming Languages



Mandarin Chinese
Taiwanese (South Accent)
English (Toeic 795)


Esun Chinese Hand-write Characters recognition - Esun Bank

Clean up the hand-write datasets from bank customer and train the recognition model.

June 2021

Career Hack Final - AI chat bot •  Microsoft x TSMC

Use Azure service to create cross-platform chatbot. Match the transaction nearby without logistics.

Jan 2021

Graduated project competition •  NTUT CSIE dept.

🏆 Honorable mention

Competition for all CS students in graduating year. We make a vehicle trajectories prediction project by SGAN, a machine learning technique. (See project Vehicle Trajectories Prediction by Machine Learning  below in detail)

Jan 2020

ACM ICPC Asia Taipei National Programming Contest for Technology Universities

🏆 Honorable mention

C++ programming contest.

Jul 2018


ISP AI Debug Tool 

Evaluate whether AI could be used to Debug MTK ISP module errors. 

Provide a tool prototype ( find the error of two modules or no error)
* High accuracy ( >= experts under one module experiment)
* Show AI can classify global and local issues of ISP bugs
Collect a raw dataset
* includes generation method and flow

Technology stack: Torch, python

Hand-craft pokemon yellow web

This project is for NTUT object oriented lab course. The rule is, using object oriented and easy framework (not a game engine, only loop) to make a comprehensive game. Finally, we spent 80 hours and got the 1st score in course.

intro web (play and github): https://nawanae.github.io/PokemonWebV2/

Technology stack: JS, css, html, canvas

OCR improvement by debluring mobile phone shot doc

This is the final project for Deep Learning and NLP Research Methodologies course, NTHU. We propose our debluring model to handle OCR blurry input. Hence, we adopt the SmartDocQA, a real-world phone took text images dataset, as our deblur dataset. After our aligment of dataset and training, finally we get better OCR accuracy.
report: https://drive.google.com/file/d/1YN7MRtP-H9nG6fFzkbsAzOiep2lWzLnj/view?usp=sharing
Technology stack: Tesseract OCR, DMPHN, pytorch, CBAM, CNN, deblury

Vehicle Trajectories Prediction by Machine Learning

The graduated project of NTUT CS dept. We cooperated with M.S. student to enhance the SGAN trajectories prediction model. Eventually, we get better predictions by extracting new features and attention in model.
Report: https://drive.google.com/file/d/1DOYCHNcQMpwV43imlYQUIwkmYVo7kjZe/view
Technology stack: pytorch, SGAN, LSTM

Tea Factory Website

This project is for NTUT web crouse final. We combine MDL with Bootstrap as our front-den. Adopted Firebase as DB system, hence the website have login and notice functions.

Github: https://github.com/a105590016/TeaWebFinal-Project

Technology stack: MDL design, BS4, firebase, javascript, html, css

Tea Transactions Website

The project for NTUT database course. We designed a tea transaction website from architecture discussions to ER diagram, from diagrams to front and back-end. We use django as back-end with SQL database. 


Technology stack: SQL, django, ER digram, js, html, css

Discord Language Learning Bot

The discord bot contains several NLP functions help users learn language. This project is for NTHU NLP lab crouse final project, finally, we get 2nd place in final competition.
1. prefix, suffix, root search in your input vocabulary
2. vocabulary using frequency search
3. sentence confidence, emotion and subjectivity check
4. scrabble
5. daily vocabulary, prefix, root and suffix
Technology stack: discord.js, nodejs, python, linggle, word2vec, gensim, pattern

Milk Volume Prediction

In this project, we use a XGBoost and Res-regression model to try to handle the milk volume prediction problem, predict milk volume by datasets include cattle information, which is raised by the TPCIIA.
1. Res-regression is better than average and the others traditional model, and get RMSE 5.8.
2. XGB regressor well fit this problem because of the data uncompleted and the small amount, finally get RMSE 5.47.
Technology stack: pytorch, pandas, Res-regrssion, XGBoost

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