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上級
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就職を希望していません
Taiwan
Taipei, Taiwan
Hsinchu City, Taiwan
Taoyuan City, Taiwan
台灣
新竹市, 台灣
IT
工業
技術
銀行／保険／金融
1年未満
1〜2年
2〜4年
4〜6年
6〜10年
10〜15年
15年以上
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National Taiwan University
National Cheng Kung University
National Tsing Hua University
國立勤益科技大學
國立台灣大學
清華大學
Georgia Institute of Technology
National Central University
National Chiao Tung University
National Chung Cheng University
Hsinchu City, Taiwan
Taiwan
台灣
新竹市, 台灣
フルタイム
JAVA
Machine Learning
PYTHON
C++
Deep Learning
Excel
Git
Linux
Natural Language Processing
PowerPoint
No
Yes
1-5 people
1ヶ月以内
1年以上
Data Scientist
Developer Team Leader, Architect, FullStack Developer
Machine Learning Engineer / Data Science Engineer
Machine Learning Researcher / Engineer
Bachelor of Engineering (BEng)
Master’s Degree
Bachelor
Master
2020
2018
2014
2011
2010
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, Coretronic Inc.
Academia Sinica
Aita International Co., Ltd
Gigabyte
JIHSUN BANK
KKBOX
KKLab, KKBOX Group
PHISON
Patentcloud Inc
Pingtong
リモートワークに興味あり
リモートワークに興味なし
パートタイムのフリーランス
English - 流暢
Chinese - ネイティブまたはバイリンガル
English - 中級者
English
Chinese
4〜6年
6〜10年
10〜15年
15年以上
National Taiwan University
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Avatar of the user.
課金ユーザー企業は利用可能
人工智慧工程師 @玉山銀行智能金融處 (Intelligent Finance Dept., E-SUN Bank )
・
2020 ~ 現在
Machine Learning Researcher / Engineer
1ヶ月以内
Research
Music Information Retrieval
Natural Language Processing
就職中
フルタイム / リモートワークに興味あり
4〜6年
National Taiwan University
・
Graduate Institute of Communication Engineering
Avatar of Kled Chen.
Avatar of Kled Chen.
Kled Chen
NAND Mechanism RD, Machine Learning Engineer @PHISON
・
2015 ~ 現在
Machine Learning Engineer / Data Science Engineer
1年以上
Kled Chen Assistant Manager (Now) Software Engineer (9 years) Algorithm Developer (6 years) Machine Learning Engineer (3 years) Physics Master Financial Researcher [email protected] Skills Power Point / Excel / Office C++ / C / Python / Git Algorithm Development / Data analyse Machine Learning / Neuron network / Tensorflow / Keras / Autoencoder / CNN Physics 學歷 NATIONAL TAIWAN UNIVERSITY, Physics Master, 2008 ~ 2010 ‧ Magnetic Quantum Confinement and Interaction of Co Nanoislands Resolved by Spin-Polarized Scanning Tunneling Microscopy and Spectroscopy ‧ 2010 Physics Annual Meeting of the Physics Best Paper in Magnetics Material
Power Point
Excel
word
フルタイム / リモートワークに興味あり
6〜10年
NATIONAL TAIWAN UNIVERSITY
・
Physics Master
Avatar of Huang Yen Chun.
Avatar of Huang Yen Chun.
Huang Yen Chun
AI enigneer @, Coretronic Inc.
・
2019 ~ 現在
1年以上
Conduct biological experiments with different type of optical spectroscopy , including total-internal-reflection spectroscopy TIRF , fluorescence spectroscopy , laser scanning confocal microscopy. AugJunMental counsultant Pingtong 298 Mechanized Infantry 學歷National Taiwan University Master Applied PhysicsNational Taiwan University Bachelor Physics 技能 Python: Scientific computing: numpy, scipy Web framework: flask, Django Machine-learning: scikit-learn, keras, gensim, tensorflow Nework investigation: networkx Javascript: cytoscape.js, highcharts.js, D3.js Database: mongodb, SQL, Postgres 語言 Mandarin. Native Fluency Taiwanese Native Fluency English. Professional Fluency(TOEFL score: reading(27), listening(24), speaking(18), writing(22)) Spanish Basic
Python
C++
AI Project Management
フルタイム / リモートワークに興味あり
6〜10年
National Taiwan University
・
Master Applied Physics
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Avatar of the user.
課金ユーザー企業は利用可能
Software Engineer @TSMC 台積電
・
2022 ~ 現在
Data Scientist
1ヶ月以内
Python
SQL
Kubernetes
就職中
・
就職を希望していません
フルタイム / リモートワークに興味なし
4〜6年
National Taiwan University
・
Economics
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Avatar of the user.
課金ユーザー企業は利用可能
Jr. Programmer @德義資訊股份有限公司
・
2013 ~ 2015
Developer Team Leader, Architect, FullStack Developer
1年以上
Word
PowerPoint
Excel
就職中
フルタイム / リモートワークに興味あり
6〜10年
National Taiwan University
・
Bachelor of Bio-Industrial Mechatronics Engineering

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Avatar of Zhao-Yang Zhuang.
Zhao-Yang Zhuang
Sr. software engineer (Full Remote) @ Gatos Vision
Gatos Vision
・
2022 ~ 現在
Taiwan
Professional Background
現在の状況
就職中
求人検索の進捗
Professions
Software Engineer, Research / R&D, Machine Learning Engineer
Fields of Employment
Manufacturing, 人工知能／機械学習, ソフトウェア
職務経験
1〜2年
Management
なし
スキル
Python
C++
Tensorflow (Keras)
OpenCV
Revit
Deep Learning
Artificial Intelligence
mechine learning
Computer Vision
Halcon
言語
Chinese
・
ネイティブまたはバイリンガル
English
・
中級者
Japanese
・
初心者
Job search preferences
希望のポジション
機器學習、資料科學工程師
求人タイプ
フルタイム
希望の勤務地
Taiwan, 台灣, Taipei, 台灣
リモートワーク
リモートワークに興味あり
Freelance
はい、私はアマチュアのフリーランスです。
学歴
学校
National Taiwan University
専攻
Civil Engineering
印刷
W8pta5tkps8w1p7ljk0l

Zhao-Yang Zhuang (莊昭陽)

Experience with computer vision, deep learning. I am very passionate about design a novel DL model architecture for real world problems and hope to participate in more types of applications.

ML engineer  Data scientist

  [email protected]       https://www.linkedin.com/in/rogan-zhuang/

  https://github.com/ZhuangRogan

Educations

National Taiwan University

Civil Engineering, Computer-Aided Engineering Group (M.S. degree)

(2018 ~ 2020)

Master Thesis: 

Deep-learning method assisted crane for sway prediction: Recurrent Kalman Network.

University@2x

Work Experiences

(Automation Services Co., LTD.)  (AI/CV Engineer)

(Feb, 2021 - Oct, 2021)
  • The main developer of AI/CV algorithm.
  • Compiled the AI/CV part of automatic fabric inspection machine alone from scratch.

Research Experiences

Deep-learning method assisted crane for sway prediction : Recurrent Kalman Network   

(Dec, 2019 - Jun, 2020)

Robotic LAB, NTU & 祐彬 Construction Co., Ltd

  • Predicting the future position of a payload by RKN to assist in the automation of crane.
  • The state of the payload system can be inferred by the combined information between the image pixels.
Key achievement: Assists the automation of the crane in a new way, and does not require any physical parameters but only image data of the payload. RKN, the new time-series forecasting architecture will be 10x better than LSTM.

Tensorflow(Keras) OpenCV Python C/C++  Deep Learning 

The second generation of automatic fabric inspection machine 

 (Feb, 2021 - Apr, 2021)

Automation Services Co., LTD.

  • Detecting the defects on the textile by deep learning that efficiency is at least ten times of manual visual inspection.
  • Calculate the area and location of defects by semantic segmentation.
  • The prototype machine can detect the width of about two meters with eight cameras.

 C# Deep Learning

The third generation of automatic fabric inspection machine 

 (May, 2021 - Oct, 2021)

Automation Services Co., LTD.

  • Based on the second-generation inspection machine, all of the features are upgraded, such as image grabbing system, camera calibration system, deep learning framework, thread optimization, etc.
  • This mass production machine is online.
  • Not implemented using Tensorflow or Pytorch.

Key achievement: 100% detection of defects required by customers, 36x8 frames per second detection speed.

C# Deep Learning Cameras System Multithread Programming

Side Projects

  • Image automatic labeling: CNN-base object tracking by Siam-Net. [labeling 90x faster than manual]
  • Document layout analyzing: locate file elements (titles, text, pictures, etc.) by image segmentation. 
  • HousePrice-prediction: Predict the HousePrice in Feature Engineering & Advanced Regression. [Kaggle top 0.04%]
  • Flowers classification: Distributed training a CNN to classify 104 kinds of flower pictures. [Kaggle top 0.09%]
Resume
プロフィール
印刷
W8pta5tkps8w1p7ljk0l

Zhao-Yang Zhuang (莊昭陽)

Experience with computer vision, deep learning. I am very passionate about design a novel DL model architecture for real world problems and hope to participate in more types of applications.

ML engineer  Data scientist

  [email protected]       https://www.linkedin.com/in/rogan-zhuang/

  https://github.com/ZhuangRogan

Educations

National Taiwan University

Civil Engineering, Computer-Aided Engineering Group (M.S. degree)

(2018 ~ 2020)

Master Thesis: 

Deep-learning method assisted crane for sway prediction: Recurrent Kalman Network.

University@2x

Work Experiences

(Automation Services Co., LTD.)  (AI/CV Engineer)

(Feb, 2021 - Oct, 2021)
  • The main developer of AI/CV algorithm.
  • Compiled the AI/CV part of automatic fabric inspection machine alone from scratch.

Research Experiences

Deep-learning method assisted crane for sway prediction : Recurrent Kalman Network   

(Dec, 2019 - Jun, 2020)

Robotic LAB, NTU & 祐彬 Construction Co., Ltd

  • Predicting the future position of a payload by RKN to assist in the automation of crane.
  • The state of the payload system can be inferred by the combined information between the image pixels.
Key achievement: Assists the automation of the crane in a new way, and does not require any physical parameters but only image data of the payload. RKN, the new time-series forecasting architecture will be 10x better than LSTM.

Tensorflow(Keras) OpenCV Python C/C++  Deep Learning 

The second generation of automatic fabric inspection machine 

 (Feb, 2021 - Apr, 2021)

Automation Services Co., LTD.

  • Detecting the defects on the textile by deep learning that efficiency is at least ten times of manual visual inspection.
  • Calculate the area and location of defects by semantic segmentation.
  • The prototype machine can detect the width of about two meters with eight cameras.

 C# Deep Learning

The third generation of automatic fabric inspection machine 

 (May, 2021 - Oct, 2021)

Automation Services Co., LTD.

  • Based on the second-generation inspection machine, all of the features are upgraded, such as image grabbing system, camera calibration system, deep learning framework, thread optimization, etc.
  • This mass production machine is online.
  • Not implemented using Tensorflow or Pytorch.

Key achievement: 100% detection of defects required by customers, 36x8 frames per second detection speed.

C# Deep Learning Cameras System Multithread Programming

Side Projects

  • Image automatic labeling: CNN-base object tracking by Siam-Net. [labeling 90x faster than manual]
  • Document layout analyzing: locate file elements (titles, text, pictures, etc.) by image segmentation. 
  • HousePrice-prediction: Predict the HousePrice in Feature Engineering & Advanced Regression. [Kaggle top 0.04%]
  • Flowers classification: Distributed training a CNN to classify 104 kinds of flower pictures. [Kaggle top 0.09%]