- Jobs
ResumeCreate your job-winning resume using our free resume builder.
PortfolioShowcase your skills and projects with a professional portfolio.ResumeCreate your job-winning resume using our free resume builder.Resume BuilderMake a resume for free.Resume TemplatesAccess our extensive library of professional & ready-to-use templates.Resume ExamplesGet inspired by real resume examples to create your own.Occupation GuideAccess resume writing guides tailored for different professions.Resume HelpGet expert advice on all things resume from our team of recruitment specialists.- ResourcesSuccess StoriesBusiness ExcellenceAbout CakeResumeFeatured Reads
- Hire
- Download our App
CakeResume Talent Search
The Most Lightweight and Effective Recruiting Plan
Search resumes and take the initiative to contact job applicants for higher recruiting efficiency. The Choice of Hundreds of Companies.
- Browse all search results
- Unlimited access to start new conversations
- Resumes accessible for only paid companies
- View users’ email address & phone numbers
Definition of Reputation Credits
Work Experience
Data Scientist Intern • AU OptronicsJuly 2022 - Sept 2022 | Research Assistant • NCKU CSIEMar 2022 - June 2022 |
• Achieved 95% accuracy in machine defect detection by training YOLOv5 and 93% on the SOTA YOLOv7 model. • Implement alarm system to notify engineers when defects are detected with Python. • Designed and developed user-friendly UI using PyQt5 to streamline label generation and model retraining, empowering non-technical users to accomplish these task with ease and efficiency. | • Utilized Python and various data analysis tools (NumPy, Pandas, Matplotlib) to implement standardized approach to bounding box labels, contributing to improved model performance. • Leveraged YOLOv5 with accuracy of up to 90% accuracy, consistently delivering reliable results. • Develop dataset auto-labeling pipeline using Python and trained YOLOv5 to increase labeled dataset. |
Education
National Taiwan University • M.S., Computer Science
Sept 2022 - Aug 2024
• Focus on SLAM & monocular 3D scene reconstruction research to improve model performance and/or reduce computational cost and develop AR application system pipeline with Unity for tele-meeting scenario.
• Related coursework: Intro to Fintech, Game Programming, Robotics, Artificial Intelligence, Advanced Computer Vision
• Average GPA: 4.0/4.3
National Cheng Kung University • B.S., Computer Science
Sept 2018 - July 2022
• NCKU x Bank Sinopac Scholarship and Encouragement Student Aid (Jan. 2021)
• Related coursework: Data Structure, Algorithms, Operating Systems, Computer Vision, Deep Learning
• Average GPA: 3.0 / 4.3
Projects
Automated Trading System / Experiment (Alpaca)
[In Progress]
• Developed an automated Python trading system with FastAPI as the backend.
• Analyzed daily profit/loss data and automated comparisons with NASDAQ.
• Employed MongoDB to store profit/loss data efficiently.
• Ongoing work: Developed a web interface to visualize profit/loss charts using HTML, CSS, and JavaScript (Chart.js).
• Ongoing work: Exploring machine learning models for stock price predictions
Blogging Content Generator with LLM
• Leveraged the cutting-edge Langchain framework to interface with GPT-3.5-turbo LLM API.
• Designed a user input pipeline system, capable of generating extensive 1500-word blog content.
• Improved pipeline efficiency by 40%, reducing inference time from 5 to 3 minutes.
• Enhance content accuracy and reduce LLM hallucination with Google SERP data scraping.
• Employed Flask framework for efficient API communication.
• Applied prompt engineering to optimize LLM output.
Weight Tracker
• Designed a weight tracking website using HTML, CSS, and JavaScript.
• Utilized Chart.js to create visually stunning weight charts.
• Developed a Node.js backend for data transmission.
• Stored and managed weight data efficiently in MySQL.
Traditional Chinese Medicine Analyzer
• Developed a mobile app for image capture and content browsing using Flutter.
• Achieved 93% accuracy in traditional Chinese medicine detection using YOLOv5.
• Employed FastAPI to interact with a custom-trained YOLOv5 model hosted on a server.
Electricity Operating Reserve Forecasting
• Employed data analysis tools (NumPy, Pandas, Matplotlib) to analyze data seasonality.
• Utilized ADF and KPSS tests to assess data stationarity.
• Conducted model comparison to identify the most effective machine learning approach.
Garbage Classification
• Captured 1200+ images across 5 garbage classes.
• Achieved 92% accuracy in garbage classification with MobileNetV2.
• Achieved 95% accuracy in garbage classification with custom ResNet50.
• Created a Flask-based backend server for image inferencing.
Skills
Programming Languages
- Python
- C / C++ / C#
- HTML / CSS / Javascript
- Flutter / Dart
- Java
Software Tools
- Keras / TensorFlow / PyTorch
- Roboflow / LabelImg
- Numpy / Pandas / Scikit-Learn
- OpenCV
- MongoDB / MySQL / SQLite
- Flask / FastAPI / Node.js
Language
- English (IELTS: 7.0)
- Chinese
- Indonesian
Work Experience
Data Scientist Intern • AU OptronicsJuly 2022 - Sept 2022 | Research Assistant • NCKU CSIEMar 2022 - June 2022 |
• Achieved 95% accuracy in machine defect detection by training YOLOv5 and 93% on the SOTA YOLOv7 model. • Implement alarm system to notify engineers when defects are detected with Python. • Designed and developed user-friendly UI using PyQt5 to streamline label generation and model retraining, empowering non-technical users to accomplish these task with ease and efficiency. | • Utilized Python and various data analysis tools (NumPy, Pandas, Matplotlib) to implement standardized approach to bounding box labels, contributing to improved model performance. • Leveraged YOLOv5 with accuracy of up to 90% accuracy, consistently delivering reliable results. • Develop dataset auto-labeling pipeline using Python and trained YOLOv5 to increase labeled dataset. |
Education
National Taiwan University • M.S., Computer Science
Sept 2022 - Aug 2024
• Focus on SLAM & monocular 3D scene reconstruction research to improve model performance and/or reduce computational cost and develop AR application system pipeline with Unity for tele-meeting scenario.
• Related coursework: Intro to Fintech, Game Programming, Robotics, Artificial Intelligence, Advanced Computer Vision
• Average GPA: 4.0/4.3
National Cheng Kung University • B.S., Computer Science
Sept 2018 - July 2022
• NCKU x Bank Sinopac Scholarship and Encouragement Student Aid (Jan. 2021)
• Related coursework: Data Structure, Algorithms, Operating Systems, Computer Vision, Deep Learning
• Average GPA: 3.0 / 4.3
Projects
Automated Trading System / Experiment (Alpaca)
[In Progress]
• Developed an automated Python trading system with FastAPI as the backend.
• Analyzed daily profit/loss data and automated comparisons with NASDAQ.
• Employed MongoDB to store profit/loss data efficiently.
• Ongoing work: Developed a web interface to visualize profit/loss charts using HTML, CSS, and JavaScript (Chart.js).
• Ongoing work: Exploring machine learning models for stock price predictions
Blogging Content Generator with LLM
• Leveraged the cutting-edge Langchain framework to interface with GPT-3.5-turbo LLM API.
• Designed a user input pipeline system, capable of generating extensive 1500-word blog content.
• Improved pipeline efficiency by 40%, reducing inference time from 5 to 3 minutes.
• Enhance content accuracy and reduce LLM hallucination with Google SERP data scraping.
• Employed Flask framework for efficient API communication.
• Applied prompt engineering to optimize LLM output.
Weight Tracker
• Designed a weight tracking website using HTML, CSS, and JavaScript.
• Utilized Chart.js to create visually stunning weight charts.
• Developed a Node.js backend for data transmission.
• Stored and managed weight data efficiently in MySQL.
Traditional Chinese Medicine Analyzer
• Developed a mobile app for image capture and content browsing using Flutter.
• Achieved 93% accuracy in traditional Chinese medicine detection using YOLOv5.
• Employed FastAPI to interact with a custom-trained YOLOv5 model hosted on a server.
Electricity Operating Reserve Forecasting
• Employed data analysis tools (NumPy, Pandas, Matplotlib) to analyze data seasonality.
• Utilized ADF and KPSS tests to assess data stationarity.
• Conducted model comparison to identify the most effective machine learning approach.
Garbage Classification
• Captured 1200+ images across 5 garbage classes.
• Achieved 92% accuracy in garbage classification with MobileNetV2.
• Achieved 95% accuracy in garbage classification with custom ResNet50.
• Created a Flask-based backend server for image inferencing.
Skills
Programming Languages
- Python
- C / C++ / C#
- HTML / CSS / Javascript
- Flutter / Dart
- Java
Software Tools
- Keras / TensorFlow / PyTorch
- Roboflow / LabelImg
- Numpy / Pandas / Scikit-Learn
- OpenCV
- MongoDB / MySQL / SQLite
- Flask / FastAPI / Node.js
Language
- English (IELTS: 7.0)
- Chinese
- Indonesian