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进阶搜寻
On
4 到 6 年
6 到 10 年
10 到 15 年
15 年以上
Machine Learning Software Engineer @AMD2021 ~ 现在
・
Machine Learning Engineer
兩個月內
deep learning. Deep Learning Engineer , CVITEK, OctSep 2021 Spin off from Bitmain . Mainly focus on deep learning accelerator (so called NPU or TPU) and stereo vision accelerator. Deep learning accelerator a. Research and prototype the int8, int4 and bf16 quantization algorithm. b. Mix-precision algorithm based on Post training, result had applied patent in US and CN (USA1, CNA). c. Model compression flow (heterogeneous quantization). d. Design quantization flow in deep learning compiler (graph optimization, calibration, fine tuning, mix-precision). e. Implement frontend of deep learning compiler (high
就职中
全职 / 对远端工作有兴趣
6 到 10 年
National Chiao Tung University
・
Computer Science
AI Engineer @Revlis Biotech Co. Ltd., Yunlin County, Taiwan2022 ~ 现在
・
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
兩個月內
Gavin Jang AI Engineer Taichung City, Taiwan Highly skilled in Machine/ Deep Learning, Statistics, Time Series Analysis, and Multivariate Analysis. Have built a WaveGAN model for generating 12 LEADs ECG signals and a U-Net model for reconstructing 12 LEADs ECG signals. Accomplishments De-Noising Auto-Encoder for ECG Signals U-Net for Reconstructing 12 LEADs ECG Signals WaveGAN for Generating 12 LEADs ECG Signals Deep Learning Model for Heart Disease Diagnosis AI-Based Blood Sugar Detection with ECG Signals Data Visualization and Deep Learning Model for Deep-Sea Fishery Work History AI Engineer Revlis Biotech Co
就职中
全职 / 对远端工作有兴趣
10 到 15 年
National Sun Yat-sen University
・
Biological Oceanography, Multivariate Analysis, Time Series Analysis 
Teaching Assistant @Georgia Institute of Technology | The University of British Columbia2014 ~ 2019
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PHD Student
超過一年
Lindsay Yuling Chuang I am a Ph.D. candidate of Geophysics at Georgia Tech. My research mainly focus on using various machine learning and deep learning algorithms to solve different seismological problems. I am a data enthusiastic with 10+ years full stack developing experiences. Atlanta, GA, USA Publication Journal paper Earthquake transformer - an attentive deep-learning model for simultaneous earthquake detection and phase picking publication dat SM Mousavi, WL Ellsworth, W Zhu, LY Chuang, GC Beroza Nature communications, 1-12 Plateau subduction, intraslab seismicity, and the Denali (Alaska) volcanic gap publication date L Chuang
Intern / 对远端工作有兴趣
6 到 10 年
The University of British Columbia
・
M.S. in Geophysics
機器學習演算法工程師
超過一年
吳杰 我畢業於交通大學電子工程研究所，目前專注於機器學習這塊領域。碩士論文主要是研究：如何在物聯網中，利用機器學習的演算法降低總能量消耗。 自己在服役期間，用Deep learning做了一些side project，例如：輸入照片，自動辨別性別與年齡，語意分析，走迷
全职 / 对远端工作有兴趣
4 到 6 年
交通大學
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電子工程系
就职中
全职 / 对远端工作有兴趣
6 到 10 年
國立台灣大學
・
經濟學就职中
全职 / 对远端工作有兴趣
6 到 10 年
IIT Bombay
・
MTech in Electronic Systems就职中
・
正在积极求职中
全职 / 对远端工作有兴趣
6 到 10 年
國立臺灣科技大學
・
電機系
Senior Software Engineer @U-NEXT Co., Ltd.2021 ~ 现在
・
Software Engineer
一個月內
Tensorflow/Keras/OpenCV Software Engineer • 盛星科技 | Astra Inc. 十二月四月Build innovative computer vision and pedestrian detection backend service - Build and maintain a high availability of deep learning-based computing systems - Develop human detection and facial recognition deep learning models and algorithms [Core technology] - Golang/Python - AWS/DynamoDB/SQS/EC2 - Tensorflow/Keras/OpenCV/openVINO Platform Engineer Intern • Intel 二月六月Survey internal paper and develop the internal script for Xeon SP testing platform - FPGA, OpenCL deep learning and machine learning research - Develop
就职中
全职 / 对远端工作有兴趣
4 到 6 年
Nation Taiwan University
・
Bioelectronic and Bioinformatics
Algorithm Engineer @Delta Electronics2017 ~ 现在
・
Algorithm Engineer
一個月內
莊承翰 The devil is in the detail. Video and Image Algorithm, Deep learning, Software development [email protected] Summary Over 8 years of experience in deep learning and more than 10 years of experience in computer vision/image processing. Capable of independently or collaboratively building AI (image/video) products from scratch with various teams. Analyzing, and improving deep learning systems. Kaggle Top 1% ( 16 /Sartorius - Cell Instance Segmentation (2021/12~2021/12) Top 4% ( 85 /Human Protein Atlas Image Classification (2018/11~2019/1
就职中
全职 / 暂不考虑远端工作
4 到 6 年
National Chin-Yi University of Technology
資料分析師 @天鏡科技
資料分析師
一年內
categorical data, text data, imbalance data. Languages Mandarin, English Experience Data Analyst - skymirror co.，AprMaydata modelling Make statistical model for daily or long term trading strategy of Taiwan, China, US future market, and oversea financial derivatives. Reviewing and improving the model. Applying financial indicator or machine learning e.g. Xgboost and RNN to predict market. And improve the model. Study new technical about deep learning or mathematical algorithm and try it on trading. Main goal is to improve model accuracy. Data visualization Communicate with manager how to calculate and decide
全职 / 对远端工作有兴趣
6 到 10 年
國立台北大學
・
統計最轻量、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)