關於我About

我目前就讀於國立中正大學電機工程研究所碩士班二年級。個性開朗樂觀，對攝影與戶外活動充滿熱忱。自高中時期起，我便對 3C 科技展現濃厚興趣，並透過自學 Visual Basic 與 SQL 開發記帳系統。這股動力驅使我自學 Python 並參與經濟部工業局的 AIGO 人才培育計畫，期間與團隊脫穎而出，獲選為前三名優秀團隊。As an Electrical Engineering Master's student at National Chung Cheng University, I possess a robust multidisciplinary background spanning Artificial Intelligence, Robotics (ROS), and Full-Stack Development. My technical journey began with a strong passion for software engineering, leading me to self-study Python and participate in the Industrial Development Bureau's AIGO talent program, where my team was distinguished as one of the top three groups.

在大學時期，我致力於機器人控制與系統整合的實務應用。大二時，我參與了與「騰安科技」的產學合作案，研究 Franka Emika Panda 機械手臂的控制技術。期間，我成功在 Ubuntu 環境下架設 ROS(機器人作業系統)，並負責撰寫包含 Linux Real-Time Kernel、ROS Noetic、libfranka 及 MoveIt 等關鍵組件的安裝與測試手冊，大幅提升了技術落地性。畢業專題則進一步整合 YOLO 物件偵測與 OpenCV 深度影像識別技術，開發出一套六軸機械手臂視覺抓取系統，實現了自動化的物件識別與移動控制。During my undergraduate studies, I actively bridged the gap between theory and practice. Through an industry collaboration with Teng-An Technology, I deployed a ROS Noetic environment on a Real-Time Linux Kernel to control a Franka Emika Panda robotic arm, significantly enhancing system integration efficiency. I further solidified my expertise in robotics through my graduation project, where I engineered a 6-DoF visual grasping system integrating YOLO and OpenCV for real-time object detection and automated control.

除了硬體整合，我也具備豐富的全端開發與系統管理經驗。我曾接受「志明牙體技術所」委託，獨立開發客製化的進出貨會計系統(ERP System)。碩士期間，我為本校通訊系開發了「物品管理系統」，並於大學甄選入學委員會擔任工讀生，運用 ELK (Elastic Stack) 進行 Log 資料分析，同時使用 PHP (CodeIgniter 4 框架) 建置「多人專案時程管理系統」，有效優化了工程團隊的工作指派流程。Beyond robotics, I have demonstrated strong capabilities in software development and system administration. I independently managed the full SDLC of a custom ERP system for a dental laboratory and developed university-level management platforms using the ELK Stack and PHP.

目前我的研究主軸聚焦於 AI 輔助天線設計，重點在於利用梯度估計網路優化貼片天線的金屬圖形，並致力於解決二值化設計限制所衍生的梯度飽和問題。此項研究成果已正式獲 URSI General Assembly and Scientific Symposium (URSI GASS 2026) 錄取接收，證明了該算法在電磁計算與優化領域的創新性與學術價值。此外，我也負責架設與維護實驗室的 NVIDIA DGX Station V100 運算平台，開發網頁介面讓使用者能透過瀏覽器輕鬆管理 Container，以支援實驗室的高效能運算需求。Currently, my research focuses on AI-driven antenna design, specifically proposing a gradient estimation network as a surrogate model to optimize patch antenna designs. I also manage the laboratory's NVIDIA DGX Station V100, overseeing containerized environments to support high-performance computing tasks.