Yi Lu Email & Phone Number

【Skills】：Programming Languages：● Python ● C/C++ ● HTML ● CSS ● JavaScriptDomains：● Web Development (Django, Flask, React.js) ● Image Processing, Natural Language Processing● Embedded Systems (FreeRTOS)Tools：● Database (MariaDB, MongoDB)● Deep Learning (TensorFlow, PyTorch, Scikit-learn)● OpenCV, Git, Docker, Streamlit, Selenium【Publications】：● Multiple Embedding Enhanced Multi-Graph Neural Networks for Chinese Healthcare Named Entity Recognition. IEEE Journal of Biomedical and Health Informatics (IEEE J-BHI). (SCI) (IF = 5.223) (Top 3.7%=1/27, in Medical Informatics) (Top 9.6%=15/156 in Computer Science, Information Systems) (Top 11%=12/109 in Computer Science, Interdisciplinary Applications)● 門控圖序列神經網路之中文健康照護命名實體辨識。第32屆自然語言與語音處理研討會 (ROCLING'20) (最佳論文獎)(Best Paper Award)● 基於圖神經網路之中文健康照護命名實體辨識。中文計算語言學期刊 (IJCLCLP)，25卷，第2期 (Special Issue on Selected Papers from ROCLING XXXII)● NCUEE at MEDIQA 2019: Medical Text Inference Using Ensemble BERT-BiLSTM-Attention Model. In Proceedings of the 18th Workshop on Biomedical Natural Language Processing (BioNLP'19), Florence, Italy, 1 August, 2019, pp. 528-532.【Awards】：● 「教育部人工智慧競賽-生醫論文自動分析熱身賽」前標獎項 (2019/03)● 台灣網路智能學會108年度最佳碩士論文獎 (2020/12)● 第32屆自然語言與語音處理研討會 (ROCLING 2020) 最佳論文獎 (2020/09)● 2022 交通數據創新應用競賽服務已上線組績優獎 (2022/06)

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  Senior Software Engineer

  Wiwynn

  Sep 2021 - Present - 台灣 新北市 汐止區

  【AI in Automated Optical Inspection (AOI) for Smart Factory Automation】● Introduction: Developed an AI-based smart inspection system for factories, focusing on model deployment, data collection, and labeling.● Objective: Aimed to reduce manual labor and enhance efficiency, ensuring consistent inspection standards and lower labor costs.● Benefits: Achieved a 75% reduction in manpower on 9 production lines, applied to 100+ product types, reducing defects by 75%. Plans for further expansion are underway.● Contributions: - AI Model Development: Streamlined training, expanded defect detection, and enhanced performance. - Data Strategy: Improved data collection and processing, reducing costs and optimizing for multi-product lines. - Platform Optimization: Advanced deployment methods, and optimized front-end and back-end systems. - Team and Process Management: Utilized GitFlow and Hackmd for efficient project management.【AI Monitoring in Product Assembly Process】● Introduction: Applied AI technology to monitor product assembly processes, enhancing the inspection system.● Objective: Increased inspection efficiency and reduced manufacturing errors through AI, improving production efficiency.● Benefits: The system effectively identifies real-time assembly issues, reducing errors and minimizing repair costs.● Contributions: Implemented Object Detection models and image processing techniques, deploying on Raspberry Pi 4.