Yao Yang, Hong 洪堯煬
browse resume online (recommend)
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
Education
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
Skills
Skills
Deep learning (NLP、CV)
Web design
Web crawler
Chat bot (Discord)
Desktop program
Software
Microsoft Office
Visual Studio Code
Git
Draw.IO
Cubase
Windows 10 / 7 / Xp
Ubuntu 16.04 / 18.04
Programming Languages
Javascript
Python
C++
C
HTML
CSS
Languages
Mandarin Chinese
Taiwanese (South Accent)
English (Toeic 795)
Competitions
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
Projects
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
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.
Functions:
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
https://github.com/kevin879275/NLP_FinalProject
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.
Results:
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
