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陳昱希 Computer Vision Engineer Yu-Hsi Chen has rich experience in developing computer vision and machine learning algorithms. In his recent work at Academia Sinica, he has focused on using machine learning to solve traditional computer vision and image / video processing problems. His developed NeighborTrack is a state-of-the-art single object tracking system in the field. During his school days, he used verilog on FPGA to implement the 3A system of the camera. website: Yu-hsi Chen (franktpmvu.github.io) Taipei City, Taiwan Yu-hsi Chen (franktpmvu.github

retraining models/in production. Working in RPA( Robotic Process Automation) team, Web Scraping(crawler) and automating routine tasks to achieve labor cost reduction. JuneMay 2020 Data Scientist Intern @ Cathay Financial Holdings. 國泰金控 Digital data & Technology (DDT, 數數發) Research into Interpretable Machine Learning and its existing algorithms. Experimented LIME & SHAP on open data. ( GitHub ) Real Estate Evaluation model – Geographical/Credit Card data gathering, cleaning, feature engineering (Hit-rate performance improved from 55% to 70%) Python Machine learning Data Pipelines Web Crawlers PyTorch, Airflow, Pandas, docker SQL Extract-Transform

鄭凱元 (Kai-Yuan Cheng) Machine Learning Engineer focusing on super resolution, object detection, and face recognition. Strongly interested in deep learning and computer vision. Graduated from National Taiwan University with Master of Mechanical Engineering. AI/ML Engineer Date of Birth: 1991/8/25 Mobile:E-mail: [email protected] LinkedIn: www.linkedin.com/in/mPROFESSIONAL EXPERIENCE Data Scientist (Computer Vision), TSMC, 2022/4 - Present Super resolution for wafer patch enhancement Computer vision algorithm development. Machine Learning Engineer (Computer Vision), VIVOTEK, 2019//4

Lin, Shu-Wei Strong background in physics and statistics. I have 4+ years work experience of implementing AI algorithms for computer vision and time series models. Taipei City, Taiwan Work Experience AI Engineer • Inventec Company Inc OctNovUse 2D object detection from images or the 3D point cloud data from mmWave radar to implement the blind spot monitoring (BSM) algorithms on embedded systems. Machine Learning Engineer • Institute for Information Industry FebSepDesigning and implementing the non-intrusive load monitoring (NILM) and behavior inference algorithms with tensorflow and keras for time series analysis. Programmer • Colatour Company Inc MayJanI

crucial aspect in clinical applications. I proactively organized a regular research study group with other lab members to progress our research . Participating in research projects : a comprehensive description is in "Project Experiences". Skills : Database buildup (SQL), Data Engineering (NumPy, SciPy, Pandas), M achine Learning (Scikit learn), Deep Learning (PyTorch, PyTorch lightning), C/C++ Biosignal Algorithm Engineer Rooti Labs Ltd. • AugustJuly 2020 Supervisor : Michael Li 黎克邁 (CEO, Rooti Labs Ltd.) The primary developer of the processing and interpretation algorithm for long-term ECG recordings. The developed algorithm significantly enhanced the

分析在Azure雲平台上進行數據分析。 對話機器人: 構建一個基於GPT服務的機器人，能夠進行自然語言對話。 LLaMA 1/2部署: 在Azure機器學習平台上部署LLaMA 1/2模型。 WebUI部署: 在Azure應用服務上發布一個物體檢測Web應用。 報告生成: 利用Spark AI和Radis進行自然

SEO for major platforms. - Large-Scale Website Project: Contributed to a high-value SaaS website launch, overseeing deployment and development. - Data Analysis & Systems : Developed GCP-centric data systems, boosting data integration and analysis. - Team Leadership & Innovation: Created a Vertex AI recommendation engine, advancing data team methodologies. EducationNational Chengchi University MS in Computer Science Thesis:Explainable Deep Learning-Based Recommendation Systems: Enhancing the Services of Public Sector Subsidy Online Platform Courses Taken: Big Data Analytics, Data mining, Reinforce Learning, Algorithm and BlockchainNational Cheng Kung University MS in Resource Engineering Thesis: Text-mining and machi...