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Oswald Wang (王俊隆)

Software Engineer
Good at converting caffeine into code. Oswald Wang 王俊隆 , a Master of Science in Computer Science graduate from National Central University. A fresh software engineer with a passion for teamwork and collaboration, experienced in a range of programming languages and development environments. Recently achieved first place in the IEEE ICME 2022 Grand Challenge in computer vision. I enjoy working on projects that challenge and expand my skills, such as deep learning and studying up-to-date with the latest technologies and trends. Believes in the power of teamwork and open communication to create effective and innovative solutions. Committed to fostering positive and productive work environments. ✏𝗦𝗞𝗜𝗟𝗟𝗦 ▪ 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐢𝐧𝐠 C / C++ / Python / C# / Javascript ▪ 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞 MySQL ▪ 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 Git / Jira / Agile ▪ 𝐂𝐥𝐨𝐮𝐝 𝐬𝐞𝐫𝐯𝐢𝐜𝐞 / 𝐅𝐫𝐚𝐦𝐞𝐰𝐫𝐨𝐤 Docker / Flask / Unity / Phaser / Windows Form / PyTorch / TensorFlow / Pandas ▪ 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐲 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 RESTful API / Database design / Unity Game Design / Object-Oriented Design / Deep Learning / Computer Vision / Model Quantization / Data Visualization 💻 𝗠𝘆 𝗪𝗘𝗕𝗦𝗜𝗧𝗘𝗦 ▪ 𝗥𝗲𝘀𝘂𝗺𝗲: https://drive.google.com/file/d/1RPDpW3-hFF0OjBozDuZipe6EXPaIzcJI/view?usp=sharing
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國立中央大學 National Central University
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國立中央大學 National Central University
Taipei, Taiwan

職場能力評價

專業背景

  • 目前狀態
    就職中
  • 專業
    後端開發人員
    大數據開發人員
    軟體工程師
  • 產業
    人工智慧 / 機器學習
    半導體
    軟體
  • 工作年資
    小於 1 年 (小於 1 年相關工作經驗)
  • 管理經歷
  • 技能
    Communication
    Natural Language Processing
    Inter-Process Communication
    Object Oriented Analysis
    Reinforcement Learning
    Machine Learning
    Database Schema
    Deep Learning
    Software Engineering
    C++
    Software Development
    Python
    Quick Learner
    Computer Vision(OpenCV)
    軟體開發
  • 語言能力
    English
    進階
    Chinese
    母語或雙語
  • 最高學歷
    碩士

求職偏好

  • 預期工作模式
    全職
    對遠端工作有興趣
  • 希望獲得的職位
    Software engineer
  • 期望的工作地點
    Taiwan
  • 接案服務
    不提供接案服務

工作經驗

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2022 聯發科技AI競賽 IEEE ICME 2022 Grand Challenge: Low‑power Deep Learning Semantic Segmentation Model Compression Competition for Traffic Scene in Asian Countries

2022年1月 - 2022年4月
4 個月
• Training Deep Learning model DDRNet to minimize the power consumption and speed on MediaTek Dimensity 9000 • Implemented Deep Learning model with Pytorch and OpenCV • Deploy PyTorch model to TensorFlow Lite with post-quantization • Ranked 1st in the competition

學歷

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Master’s Degree
Computer Science
2020 - 2022
簡介
- Lead author of paper of Low-power Deep Learning Semantic Segmentation Model Compression Competition for Traffic Scene in Asian Countries, IEEE ICME 2022 Grand Challenge - Co-author of paper of Portable VR-based Concussion Diagnostics of Mild Traumatic Brain Injury, IEEE Eurasia Conference on IOT, Communication and Engineering
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Bachelor of Science (BS)
Computer Science
2015 - 2019

資格認證

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TOEIC® Listening and Reading Test : 830

Educational Testing Service (ETS)
發照日期 2021年12月
永久有效