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职场能力评价定义
Pei-Jie Wang
TaiHao Medical Inc. | AI/ML Engineer - Medical Imaging
Soochow University | Bachelor of Science in Physics
+886 988620772
Projects
API Development: Breast Ultrasound Computer-Aided Detection
AI Automatically Detects the Location of Breast Ultrasound Lesions
Data Augmentation Using Learned Transformations for One-shot Biomedical Image Segmentation of Five Regions In Mouse Brain
An Accurate Segmentation Method based on Deep Convolutional Neural Networks for Functional Regions in Mouse Brain
An Automatic Neuronal Morphology Segmentation Method for Identification of Dendritic Spines
A Development of High-Content Subcellular Image Processing DLL (Co-worker: Yi-De Chen)
Skills
Machine Learning
- Yolo
- U-Net
- Transfer Learning
- Machine Learning
(TensorFlow, Keras, Pytorch)
Computer Vision
- OpenCV
- Image Segmentation
- Image Recognition
- Algorithm Development
#Python #Software Programming #C++
Software Integration
- Docker
- PyInstaller
- Cython
- Python
- Linux
#Python #Linux #Software Programming
Cascade API
- Python Flask
- Postman API
- Python
#Python #Software Integration Test #Function Test
Software and Hardware Integration
- C++
- LabVIEW
- Python
- DLL
#C++ #LabVIEW #Visual Studio
iOS APP
- Xcode
- Swift
#iOS #SWIFT #Software Programming
Work Experience
AI/ML Engineer - Medical Imaging • TaiHao Medical Inc., Taiwan
Aug 2020 - Present
1. Develop the AI that automatically detects the location of breast ultrasound lesions.
2. Optimize the AI model. By improving the sensitivity and decreasing the FP (False Positive). Moreover, accelerate the software programming.
3. Deploy the AI model to other system environments.
4. Develop an API for breast ultrasound computer-aided detection. Collaborate with front-end engineering and assist in software integration to productized service software.
5. Collaborate with foreign engineers, launching our products abroad.
Undergraduate Research Assistant • Institute of Atomic and Molecular Sciences, Academia Sinica, Taiwan
Mar 2018 - Feb 2019
1. Develop the AI image segmentation model by using machine learning and deep learning.
2. Develop image recognition-related products and applications for the laboratory by using computer vision to detect the specific part.
3. Improve the neural network model to adapt to the high complexity of medical imaging and other related issues.
4. Develop image segmentation and recognition algorithms, and produce a dynamic-link library to integrate into an opto-electro-mechanical system.
Publication
1.
Wang, P.-J., Chou, S.-J., Liao, J.-C.(2020) One-Shot transfer learning of region of mouse brain. 2020 Focus on Microscopy, Japan
2.
Zhang, X., Li, Z., Wang, P.-J., Liao, K.Y. Chou, S.-J., Chang, S.-F., Liao, J.-C.(2019) One-shot learning for function-specific region the segmentation in mouse brain. Proceedings of 2019 IEEE 15th International Symposium on Biomedical Imaging, Italy
3.
Chen, Y.-D., Chang, C.-W., Chung, C.-W., Wang, P.-J., Kai, H.-J., Luo C.-H., Yu, H.-H., Liao,J.-C.(2018) High-throughput, in-situ photoaffinity tagging of biomolecules via [Ru(bpy)3]2+ and two-photon microscopy. 2018 7th EuCheMS Chemistry Congress, UK
Awards & Honors
1.
Dec 2019
Excellence Award (Top 5), Innovation Services Group, 2019 CTCI (China Technical Consultants Inc.) Foundation Artificial Intelligence Innovation Competition in Taiwan
2.
Dec 2019
Academic Excellence Award, Ranked #1 in the Department of Physics, Soochow University, 2019 Spring semester
3.
May 2019
Academic Excellence Award, Ranked #1 in the Department of Physics, Soochow University, 2018 Fall semester
4.
Dec 2018
Academic Excellence Award, Ranked #1 in the Department of Physics, Soochow University, 2018 Spring semester
5.
May 2018
Academic Excellence Award, Ranked #3 in the Department of Physics, Soochow University, 2017 Fall semester
Pei-Jie Wang
TaiHao Medical Inc. | AI/ML Engineer - Medical Imaging
Soochow University | Bachelor of Science in Physics
+886 988620772
Projects
API Development: Breast Ultrasound Computer-Aided Detection
AI Automatically Detects the Location of Breast Ultrasound Lesions
Data Augmentation Using Learned Transformations for One-shot Biomedical Image Segmentation of Five Regions In Mouse Brain
An Accurate Segmentation Method based on Deep Convolutional Neural Networks for Functional Regions in Mouse Brain
An Automatic Neuronal Morphology Segmentation Method for Identification of Dendritic Spines
A Development of High-Content Subcellular Image Processing DLL (Co-worker: Yi-De Chen)
Skills
Machine Learning
- Yolo
- U-Net
- Transfer Learning
- Machine Learning
(TensorFlow, Keras, Pytorch)
Computer Vision
- OpenCV
- Image Segmentation
- Image Recognition
- Algorithm Development
#Python #Software Programming #C++
Software Integration
- Docker
- PyInstaller
- Cython
- Python
- Linux
#Python #Linux #Software Programming
Cascade API
- Python Flask
- Postman API
- Python
#Python #Software Integration Test #Function Test
Software and Hardware Integration
- C++
- LabVIEW
- Python
- DLL
#C++ #LabVIEW #Visual Studio
iOS APP
- Xcode
- Swift
#iOS #SWIFT #Software Programming
Work Experience
AI/ML Engineer - Medical Imaging • TaiHao Medical Inc., Taiwan
Aug 2020 - Present
1. Develop the AI that automatically detects the location of breast ultrasound lesions.
2. Optimize the AI model. By improving the sensitivity and decreasing the FP (False Positive). Moreover, accelerate the software programming.
3. Deploy the AI model to other system environments.
4. Develop an API for breast ultrasound computer-aided detection. Collaborate with front-end engineering and assist in software integration to productized service software.
5. Collaborate with foreign engineers, launching our products abroad.
Undergraduate Research Assistant • Institute of Atomic and Molecular Sciences, Academia Sinica, Taiwan
Mar 2018 - Feb 2019
1. Develop the AI image segmentation model by using machine learning and deep learning.
2. Develop image recognition-related products and applications for the laboratory by using computer vision to detect the specific part.
3. Improve the neural network model to adapt to the high complexity of medical imaging and other related issues.
4. Develop image segmentation and recognition algorithms, and produce a dynamic-link library to integrate into an opto-electro-mechanical system.