CakeResume 找人才
进阶搜寻
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
Taichung City, Taiwan
Data engineer @H2 Inc.2021 ~ 现在
・
AI engineer, ML engineer, data scientist
三個月內
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
就职中
・
目前会考虑了解新的机会
全职 / 对远端工作有兴趣
4 到 6 年
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
一個月內
就职中
・
目前会考虑了解新的机会
全职 / 对远端工作有兴趣
4 到 6 年
National Yang Ming Chiao Tung University
・
Computer Science
資深經理 @緯創資通2021 ~ 现在
・
Technical Manager
半年內
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
就职中
全职 / 对远端工作有兴趣
10 到 15 年
National Taiwan University of Science and Technology
・
Master's degree Computer Science and Information Engineering最轻量、快速的招募方案，数百家企业的选择
搜寻简历，主动联系求职者，提升招募效率。
- 浏览所有搜寻结果
- 每日可无限次数开启陌生对话
- 搜尋僅開放付費企業檢視的简历
- 检视使用者信箱 & 电话
搜寻技巧
1
Search a precise keyword combination
senior backend php
2
Use quotes to search for an exact phrase
"business development"
3
Use the minus sign to eliminate results containing certain words
UI designer -UX
职场能力评价定义
专业技能
该领域中具备哪些专业能力（例如熟悉 SEO 操作，且会使用相关工具）。
问题解决能力
能洞察、分析问题，并拟定方案有效解决问题。
变通能力
遇到突发事件能冷静应对，并随时调整专案、客户、技术的相对优先序。
沟通能力
有效传达个人想法，且愿意倾听他人意见并给予反馈。
时间管理能力
了解工作项目的优先顺序，有效运用时间，准时完成工作内容。
团队合作能力
具有向心力与团队责任感，愿意倾听他人意见并主动沟通协调。
领导力
专注于团队发展，有效引领团队采取行动，达成共同目标。
专业背景
目前状态
待业中
求职阶段
专业
软体工程师, Python 开发人员, 机器学习工程师
产业
人工智能 / 机器学习, 软件, 资讯服务
工作年资
小於 1 年
管理经历
无
技能
语言能力
求职偏好
希望获得的职位
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
预期工作模式
全职
期望的工作地点
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
远端工作意愿
对远端工作有兴趣
接案服务
否
学历
学校
國立台灣科技大學
主修科系
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)