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Avatar of 鄭翔元（Denny Cheng）.
Avatar of 鄭翔元（Denny Cheng）.
鄭翔元（Denny Cheng）
Past
資深工程師 @Velodash Inc.
・
2019 ~ 2023
Android / Flutter / Backend
Dalam satu bulan
Denny Cheng ( 鄭翔元 ) I am a software engineer with diverse skills. From 2016 to 2018, I was responsible for Android and backend development (Python Flask). From 2019 to 2023, my main focus was on Flutter and React. In addition, I also use C# for side project development. My skill set spans across the development of applications for various platforms, and I maintain a curious and learning-oriented attitude towards new technologies. Taipei, Taiwan [email protected] EducationNational Cheng Kung University ( 國立成功大學 ) Computer Science and Information
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kotlin
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國立成功大學
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django
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高雄應用科技大學
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Engineer @鴻霖
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2022 ~ Sekarang
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後端工程師 @Glossika
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2022 ~ Sekarang
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Laravel
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Henpai Hsu
前端工程師 @美商塗鴉科技(PRO360)
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React-Hook-Form / React-Reactive-Form / GraphQL / NextJS Senior Frontend | Positivegrid , DecSep 2020 Develop campaign page with Bigcommerce, handlebars, stencil in vanilla Javascript Redesign architecture for service migration, from Heroku + GCP to both Ali-cloud and AWS Migrate Firebase Firestore to MongoDB Develop new APIs in Flask(Python) with other DSP engineer Introduce Docker and create create Linux CLI tool docker environment for audio process Dockerfy several backend servers for the K8S cluster Analyze traffic by Newrelic and Papertrail Frontend | Positivegrid , DecDec 2019 Implement various MVPs with designers in React SSR Add PWA ability to the
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亓瑋漢
後端工程師 @CYBERBIZ 順立智慧股份有限公司
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灣林產品生產追溯系統 ：Laravel、vue.js 全端開發與維護、需求訪談 production 異常處理 天下雜誌出版社｜資深工程師，2018 // 12 技能：php(Laravel), python(flask, Django), node.js(koa), vue.js, GCP, Docker 於 IT 部門擔任後端工程師，負責產品功能開發、 ERP 金流串接、AI 模型產品化等工作 2020台灣總統
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資訊管理
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簡至善
Corp. IT Data Engneer @Morrison Express Corp.
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Python Developer
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statistical modeling. Passionate about streamlining ETL processes and optimizing infrastructure. Seeking data-driven roles using Python, AWS and APIs to extract value from data. LinkedIn CakeRsume Work Experience 三月Present Data Engineer Morrison Express Proficient software engineer with over 7 years of experience developing applications with Python Migrated 10+ ETL dataflows from ECS schedulers to SNS-SQS-Lambda architecture. Maintained 5+ API services using Python and Docker. Made key contributions to achieve over 90% test coverage on collaborative projects with pytest. Known for well-structured, readable code utilizing Flask, SQLAlchemy, Requests
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陳東坤
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暇時間喜歡研究新技術自我補充專業知識，目前專精於Web相關應用程序，後端使用過C#(Prism、MVC、ABP)、Java(SSM、Spring boot、Spring cloud)、NodeJs(Express)、PHP(Laravel)、Python(Flask、Django)，前端Vue、React、JQuery，資料庫MSSQL、MySQL、Oracle、PostgreSQL、Sqlite，NoSQL Redis、MongoDB，其他Docker、k8s、ELK、MQTT、RabbitMQ...，期待有更多實際工作經歷。 工作經歷 軟體工程師CS
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Frontend Developer @KICKcreative - 稽古創意行銷有限公司
・
2019 ~ 2023
後端工程師、Python工程師、AI軟體工程師、前端工程師
Dalam enam bulan
能夠更專注在提供美食上。 以下是過程中自己有使用到的技術 / 技能： 前端 Vue 3 ( Axios, Vuex, Vue-router, Vue-i18n ) Ant Design Vue SCSS LINE Front-end Framework (LIFF) 後端 Python Flask ( ORM 框架使用 Flask-SQLAlchemy ) LINE Messaging API MySQL 版控 / 環境建置 Docker GitHub 工作經歷 四月三月 2023 Frontend Developer 稽古創意行銷有限公司 任職期間依照需
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緯育TibaMe
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Jason Chung
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・
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處方之關聯性及群集 利用Tableau視覺化呈現 工作 ： 資料清理、倉儲 利用機器學習（Apriori、K-Means、LDA）演算法實作關聯性分析和分群 技術 ：Python、Flask、MySQL、Highcharts、jQuery、Bootstrap 學歷二，2015 年 4 月年 10 月 中壢資策會 大數據資料分析師養成班 專題 ： 住屋區位探索 內容 ： 資料收集：撰寫爬蟲
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淡江大學 Tamkang University
・
數學系

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Benedictus Kent Chandra
Graduate student @ NTU
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2022 ~ 2022
Taipei, Taiwan
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Computer Science
Cetak

Benedictus Kent Chandra

  Taipei City, Taiwan      

Work Experience

Data Scientist Intern  •  AU Optronics

July 2022 - Sept 2022

Research Assistant  •  NCKU CSIE

Mar 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
CV
Profil
Cetak

Benedictus Kent Chandra

  Taipei City, Taiwan      

Work Experience

Data Scientist Intern  •  AU Optronics

July 2022 - Sept 2022

Research Assistant  •  NCKU CSIE

Mar 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