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in distributed computing, optimizing code execution across thousands of systems to significantly improve processing speed and efficiency. ◆Developed sophisticated data visualization tools to distill complex datasets into actionable insights, aiding strategic decision-making. The University of Tokyo, Foreign Researcher (OctSep◆Pioneered a neural network-based approach for cell image classification and data visualization, enhancing lab capabilities in biological research. ◆Designed a user-friendly GUI for neural network model training, democratizing access to advanced computational tools for non-programmers. Education National Chiao-Tung University, Ph.D. - Photonics, 2015 ~ 2020 Development of Intelligent Wearable Near Infrared Spectroscopy

based Project using SIMATIC SSignal conditioning of data received from the Aircraft Engine MFI-17 Super Mushshak Part Task Trainer (Simulator) Team lead of the Hardware installation and interfacing with soft instruments Using National Instruments NI-Daq 6343 Hardware designing of Trim Panel using Arduino Uno Foreign Object Debris Detection, Classification, and Localization using Deep Learning Python language based Project using YOLO-V7 (you only look once) Addressed the Class imbalance in FOD-A Dataset FOD detection/localization with improved accuracy Data Acquisition design and implementation of a Level-D Simulator (C130-H) NI-PXI Chassis-based DATA ACQUISITION

顧少齊 設備專案工程師 Kaohsiung City, Taiwan 在部門中，我為封裝打線機台負責人角色，同時領導一支由大約10人組成的精英團隊。我的主要職責不僅限於確保機台運作的高效與可靠，還包括對於設備的定期維護與緊急修理，以防止生產中斷並最大化生產

氣道擴散偵測競賽 I：運用物體偵測作法於找尋STAS, 2022/06/02 - Bronze medal (team): (Kaggle) VinBigData Chest X-ray Abnormalities Detection: Automatically localize and classify thoracic abnormalities from chest radiographs, 2021/03/30 Classification (影像分類): - Bronze medal (solo): (Kaggle) Human Protein Atlas - Single Cell Classification: Find individual human cell differences in microscope images, 2021/05/12 - 5th place (team): (Aidea AI CUP) Mango grade classification, 2020/12/29. https://reurl.cc/

detection, segmentation, and classification AI scenario. Good communication skills with doctors' demands and collaboration with colleagues. Patent Disclosure: Ultrasound detect and notify system. (serial number: I學歷 SepJun 2 National Taiwan University of Science and Technology Masters in Electrical Engineering Thesis "Online Data Stream Analytics for Dynamic Environments Using Self-Regularized Learning Framework", IEEE journal SepJun 2020 Yuan Ze University Bachelor in Electrical Engineering Skills Customer/VC negotiation and customer services DL/ML/AI algorithm, keen problem solving 3D modeling (Blender) Python, Matlab, Tensorflow, Keras Object detection, Classification, [email protected]

modules：Resblock, GhostBottleNeck, SE-layer, DarkBlock. Used Attention mechanism：StripPooling, MixedPoolingModule, SelectiveKernel . According to the input data, use convolutional layers of different dimensions (1D~3D) to learn information. Used weight standardization to assign weights to improve model training effect. Built a composite model of regression and classification. AI development environment management Used docker or Anaconda to establish and maintain the development environment with GPU. Set up the environment to use the LLM (LLAMA2, Taiwan-LLaMa, Codellama, Llama2-chinese-13b, etc.) Model Training and Tuning Tips Adjusted the data batch size according to the

data. I've hands-on experience on building Generative Adversarial Network, many solution for various situation, to build apporpriate model for task. ii. Abnormal machine signal classifition and detection. I build apporpriate model for task whether training data has abnormal signal or not, i.e classification model or health model. iii. Administrator of Engineering Data Analysis system. I co-work with multi-functional teams to manage project scope, known their requirement and current difficulty, and guide end-user to establish their own analysis flow, thus reducing and replacing many daily manual analysis