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Taichung City, Taiwan
Data engineer @H2 Inc.2021 ~ Présent
・
AI engineer, ML engineer, data scientist
Dans 3 mois
on validation dataset. Accuracy 達到 93%, 已與醫師合作發表醫學 paper 3. Pathology案件 -建立 two stage segmentation model, stage one segmentation model 達到86% IOU, stage two segmentation model 達到 94% custom dice coefficient 學歷 清華大學 動力機械工程學系技能 Software AWS Airflow Dagster Docker Git Flask Pytorch Tensorflow DVC Languages Python SQL Bash-Shell script C/C++ Javascript Technical Skill Data Modeling Custom ETL Development Data Analysis System Resource Analysis AWS IaaS
Employé
・
Ouvert à de nouvelles opportunités
Temps plein / Intéressé par le travail à distance
4 à 6 ans
清華大學
・
動力機械工程學系
Senior AI Research/Engineer (part-time) @NeuroBonic Inc.2022 ~ 2023
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Dans 1 mois
Employé
・
Ouvert à de nouvelles opportunités
Temps plein / Intéressé par le travail à distance
4 à 6 ans
National Yang Ming Chiao Tung University
・
Computer Science
資深經理 @緯創資通2021 ~ Présent
・
Technical Manager
Dans 6 mois
林昭源 (Leo Lin) 1. Two years of management experience. 2. More than 10 years of computer vision and deep learning/software architecture development experience. 3. Programming experience using python. 4. Good paper reading ability and practical ability 5. Familiar with computer vision, deep learning (CNN, Resnet, densnet, GAN), object detection (Yolo series, RCNN series), segmentation models (UNet, DensUNet). 6. Experience in semi-supervised or unsupervised learning (pesudo labeling, Voxmorph model). 7. Experience with Docker, Git, Jenkins DevOps. Education: National Taiwan University of Science and
Employé
Temps plein / Intéressé par le travail à distance
10 à 15 ans
National Taiwan University of Science and Technology
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Definition of Reputation Credits
Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
Problem-Solving
Ability to identify, analyze, and prepare solutions to problems.
Adaptability
Ability to navigate unexpected situations; and keep up with shifting priorities, projects, clients, and technology.
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Software Engineer, Python Developer, Machine Learning Engineer
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Intelligence Artificielle / Machine Learning, Logiciel, Information Services
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AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
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Temps plein
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台灣台北, 台灣新北市, 台灣桃園, 台灣新竹, 台灣苗栗, 台灣台中
Travail à distance
Intéressé par le travail à distance
Freelance
Non.
Éducation
École
國立台灣科技大學
Spécialisation
AI
莊才賢,Cai-Xian(John) Zhuang
[email protected]
+886-983-865-151
About Me
- I graduated from the master of AI group in National Taiwan University of Science and Technology. I like to use AI models to solve some problems that especially focus on computer vision and some image processing.
- I like to challenge the impossible, and I am curious about new knowledge.
- I am looking for a software engineer for a company where I can apply my abilities to help my team to achieve what clients want.
Education & Experience
National Taiwan University of Science and Technology, M.S., Electrical Engineering- AI, Jul. 2019 - Sep. 2021
- Courses included: Machine Learning, Algorithm, Deep Learning, Image and Video Processing
- Research: Video-Based Blood Pressure Estimation Using Two-Step Learning in 3D-CNN
- Predicting ages by faces achieves only 4.2 ages error.
- Predicting gender by faces achieves approximately 98% accuracy.
- Subjects included: Program Designing, Control System, Deep Learning Application Machine Learning
- Eighth place in the whole department
Skills
Language
- Python
- C++
- Arduino
- MATLAB
IDE/Editor Tool
- Jupyter Notebook
- Spyder3
- PyCharm
- Code::Blocks
- Visual Studio
- GitHub
Cloud Service & Database
- Google Colab
- MySQL
Other Knowledge
- AI (Artificial Intelligence)
- Image Preprocessing
- Algorithm
Projects
1.Video-Based Blood Pressure Estimation Using Two-Step Learning in 3D-CNN
We used only face frames to estimate blood pressure with a normal webcam. We proposed two training skills and a two-step learning method to reduce the loss. We finally achieve 6.95/6.53 mmHg (MAEs for SBP/DBP) and 7.50/6.29 (standard deviation for SBP/DBP) which pass the criteria of AAMI.
- Language : Python
- API : Pytorch, Matplotlib, Pandas, cv2, PIL
2.Voice to Sign Language Translation System
Customer says some words. Microphone will collect them. Computer will show the Sign Language films to the hearing-impaired people.
- Language : Python
- API : SpeechRecognition, jieba, Tkinter, cv2
3.The Simpsons Characters Recognition Challenge
We used Simpson dataset and CNN architecture as the model of training and prediction.
- Language : Python
- API : Keras, Matplotlib, Pandas, sklearn, cv2
4.Score Your Face
We used SCUT-FBP5500_v2 dataset and ResNet50 architecture as the model of training and score people’s faces.
- Language : Python
- API : Keras, Matplotlib, Pandas, sklearn, cv2
5.Smart Parking Lot
We combined Arduino and Python to build Smart Parking Lot. We used Arduino to be our warning light, sensors, motors and management system. Using Python to detect and identify license plate.
- Language : Arduino, Python
- API : Keras, Matplotlib, Pandas, sklearn, cv2
Contests
- Participate in 2019 11th IT help ironman competition (AI & Data)
- 2018 NTUT Senior Project Contest - The High Distinction Award
- Participate in 2017 TEL Robot Combat final contest(東京威力科創機器人大賽)
莊才賢,Cai-Xian(John) Zhuang
[email protected]
+886-983-865-151
About Me
- I graduated from the master of AI group in National Taiwan University of Science and Technology. I like to use AI models to solve some problems that especially focus on computer vision and some image processing.
- I like to challenge the impossible, and I am curious about new knowledge.
- I am looking for a software engineer for a company where I can apply my abilities to help my team to achieve what clients want.
Education & Experience
National Taiwan University of Science and Technology, M.S., Electrical Engineering- AI, Jul. 2019 - Sep. 2021
- Courses included: Machine Learning, Algorithm, Deep Learning, Image and Video Processing
- Research: Video-Based Blood Pressure Estimation Using Two-Step Learning in 3D-CNN
- Predicting ages by faces achieves only 4.2 ages error.
- Predicting gender by faces achieves approximately 98% accuracy.
- Subjects included: Program Designing, Control System, Deep Learning Application Machine Learning
- Eighth place in the whole department
Skills
Language
- Python
- C++
- Arduino
- MATLAB
IDE/Editor Tool
- Jupyter Notebook
- Spyder3
- PyCharm
- Code::Blocks
- Visual Studio
- GitHub
Cloud Service & Database
- Google Colab
- MySQL
Other Knowledge
- AI (Artificial Intelligence)
- Image Preprocessing
- Algorithm
Projects
1.Video-Based Blood Pressure Estimation Using Two-Step Learning in 3D-CNN
We used only face frames to estimate blood pressure with a normal webcam. We proposed two training skills and a two-step learning method to reduce the loss. We finally achieve 6.95/6.53 mmHg (MAEs for SBP/DBP) and 7.50/6.29 (standard deviation for SBP/DBP) which pass the criteria of AAMI.
- Language : Python
- API : Pytorch, Matplotlib, Pandas, cv2, PIL
2.Voice to Sign Language Translation System
Customer says some words. Microphone will collect them. Computer will show the Sign Language films to the hearing-impaired people.
- Language : Python
- API : SpeechRecognition, jieba, Tkinter, cv2
3.The Simpsons Characters Recognition Challenge
We used Simpson dataset and CNN architecture as the model of training and prediction.
- Language : Python
- API : Keras, Matplotlib, Pandas, sklearn, cv2
4.Score Your Face
We used SCUT-FBP5500_v2 dataset and ResNet50 architecture as the model of training and score people’s faces.
- Language : Python
- API : Keras, Matplotlib, Pandas, sklearn, cv2
5.Smart Parking Lot
We combined Arduino and Python to build Smart Parking Lot. We used Arduino to be our warning light, sensors, motors and management system. Using Python to detect and identify license plate.
- Language : Arduino, Python
- API : Keras, Matplotlib, Pandas, sklearn, cv2
Contests
- Participate in 2019 11th IT help ironman competition (AI & Data)
- 2018 NTUT Senior Project Contest - The High Distinction Award
- Participate in 2017 TEL Robot Combat final contest(東京威力科創機器人大賽)