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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 EngineerDeep Learning Engineer、Data Scientist
En un mes
Python
R
Natural Language Processing (NLP)
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A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
國立政治大學(National Chengchi University)
資訊科學系
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Past
Data Engineer @Rooit Inc. (XO App)
2023 ~ 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 EngineerDeep Learning Engineer、Data Scientist
En un mes
Python
Data Analysis
Data Science
Desempleado
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A tiempo completo / Interesado en trabajar a distancia
6-10 años
中國醫藥大學(China Medical University)
臨床醫學研究所
Avatar of Chun-Jung Huang.
Avatar of Chun-Jung Huang.
OPC Chief Engineer @TSMC
2020 ~ Presente
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 EngineerDeep Learning Engineer、Data Scientist
En un mes
Chun-Jung Huang [email protected] Chiao-Tung University, Ph.D. - Photonics,2015 ~ 2020 Member of The Phi Tau Phi Scholastic Honor Society of the Republic of China. Work Experience TSMC, OPC Chief Engineer (MarPresent) ◆Introduced image anomaly detection techniques to identify and address defects in photomask manufacturing, significantly improving product quality and reducing turnaround time. ◆Managed large-scale data processing tasks, demonstrating expertise in analyzing and handling datasets of hundreds of millions, to bolster model development and optimization. ◆Excelled in distributed computing, optimizing code execution across thousands of systems to
Deep learning with TensorFlow
Translational Research
Clinical Research
Empleado
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A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
National Chiao-Tung University
Ph.D. - Clinical Engineering
Avatar of 潘揚燊.
Avatar of 潘揚燊.
智慧製造全端開發工程師 @聯華電子股份有限公司
2022 ~ Presente
AI工程師、機器學習工程師、深度學習工程師、影像演算法工程師、資料科學家、Ai Application Engineer,Machine Learning Engineer,Deep Learning Engineer,Data Scientist
En un mes
潘揚燊 ㄕㄣ Shen Pan Kaohsiung City,Taiwan •  [email protected] 希望職務:人工智慧、機器視覺應用開發工程師 現任 : 聯華電子 RPA 平台全端開發工程師 您好,我是潘揚燊,目前任職於 聯華電子 , 擔任 智慧製造 全端開發工程師 , 畢業於元智大學工業工程與管理學系研
Python
Qt
Git
Empleado
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A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
元智大學 Yuan Ze University
工業工程與管理學系所
Avatar of Nelson Chen.
Avatar of Nelson Chen.
Senior engineer @Chicony Electronics Co, Ltd.
2018 ~ Presente
全端工程師、後端工程師、前端工程師、軟體專案主管、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 EngineerDeep Learning Engineer、Data Scientist
En un mes
Nelson Chen Senior engineer Dedicated Software Engineer with 6+ Years of Experience Senior software engineer specializing in web page development and deep learning. Proficient with machine learning technologies, such as TensorFlow, Numpy, etc. Experience Senior engineer • Chicony Electronics Co, Ltd. .Build an Auto-Encoder AI model for defective detection. .Build an object detection model for detecting car types. .Developed a Front-End and Back-End website for data analysis. .Manage the production process and make it automated production. NovPresent Software engineer • Teco image systems co. ltd .Developed and maintained MFP driver
Python
C
C++
Empleado
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A tiempo completo / Interesado en trabajar a distancia
6-10 años
National Taiwan Ocean University
Computer science and engineering
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Avatar of the user.
全端工程師 @中冠資訊股份有限公司
2021 ~ Presente
網站後端工程師
En un mes
Vue.js
Node.js / Express.js
k8s
Empleado
Listo para la entrevista
A tiempo completo / Interesado en trabajar a distancia
6-10 años
清華大學 National Tsing Hua University
核子工程 nuclear engineering
Avatar of chiyun chao.
Avatar of chiyun chao.
Research & Development Engineer @三竹資訊股份有限公司
2023 ~ Presente
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 EngineerDeep Learning Engineer、Data Scientist
En un mes
following experience: - backend framework: Spring boot, Flask - familiar with DB syntax for Elasticsearch, PosgresSQL and MSSQL Taiwan E-mail: [email protected] Skill languages Python JAVA backend Spring Boot Flask Deep Learning Pytorch CI/CD Docker Git SVN Jenkins Work Experience 工作經歷 Research & Development Engineer Mitake Information Corporation • JulPresent LLM-Based conversation system R&D Retrival Augmented Generation (RAG) system development ReAct prompting system development OpenSource LLM inference/prompting engineering Software Engineer Gorilla Technology Group • OctMay 2023 Main Role / Achievement: Research machine learning topics such as natural language processing (NLP) and deep
Python
JAVA
Linux
Empleado
Abierto a oportunidades
A tiempo completo / No está interesado en trabajar a distancia
De 4 a 6 años
國立中央大學 National Central University
資訊工程
Avatar of Shammi HSIEH.
Avatar of Shammi HSIEH.
資訊人員 @新北市淡水區公所
2023 ~ Presente
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 EngineerDeep Learning Engineer、Data Scientist
En un mes
謝慧珊 目前就職於公家機關擔任資訊人員,熱愛閱讀與寫作, 即將於致理科技大學進修商務智慧與創新科技研究所碩士班, 研究範圍為AI創新科技領域。 個性情感充沛並且喜歡觀察人群與反思,勇於接受挑戰。 座右銘: 樂觀積極,感恩惜福 www.shammixxd159
office
Python
WordPress
Empleado
Abierto a oportunidades
A tiempo completo / Sólo a distancia
10-15 años
致理科技大學
資訊管理系
Avatar of Chin Ya Chang.
Avatar of Chin Ya Chang.
Senior Software Engineer @International Integrated Systems, Inc.(IISI)
2020 ~ Presente
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 EngineerDeep Learning Engineer、Data Scientist
En un mes
Chin Ya Chang Machine Learning Engineer New Taipei City , Taiwan [email protected] Current Position: AI Team - Software Engineer at the Central Weather Bureau, specializing in machine learning. Tasks include image generation, numerical prediction, data calibration, recommendation systems, and text generation using data from satellites, radar, and geographic information. I stay updated on AI advancements by studying research papers and implementing new approaches into projects. Recently, I've focused on deploying Large Language Models (LLM) in customer-oriented chatbots. Proficient in Docker for establishing and maintaining development environments, deploying projects to client environments.
Python
PyTorch
Machine Learning
Empleado
Abierto a oportunidades
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
私立中原大學 Chung Yuan Christian University
環境工程
Avatar of Trang Cá Cược Bóng Đá.
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 EngineerDeep Learning Engineer、Data Scientist
En el plazo de dos meses
Top 10 trang cá độ bóng đá uy tín nhắt Việt Nam. Review nền tảng cá cược trực tuyến cho những ai chưa tìm được web cá độ qua mạng phù hợp 351 Đ. Lê Đại Hành, Phường 13, Quận 11, Thành phố Hồ Chí Minh, Việt Nam#trangcacuocbongda #Trang_Cá_Độ_Bóng_Đá #Trang_Cá_Cược_Bóng_Đá https://trangcacuocbongda.app/ https://www.youtube.com/channel/UCoJT7RDFAl5RfBiA0tUtMYg/about https://www.reddit.com/user/trangcacuocbongdaapp/ https:/
Excel
Communication
Photoshop
Estudiando
Abierto a oportunidades
A tiempo parcial / No está interesado en trabajar a distancia
De 4 a 6 años

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En un año
Machine Learning Engineer
Logo of Taiwan AI Labs.
Taiwan AI Labs
2019 ~ Presente
Taipei, 台灣
Professional Background
Situación actual
Empleado
Progreso en la búsqueda de empleo
No está abierto a oportunidades
Professions
Machine Learning Engineer, Data Scientist
Fields of Employment
Inteligencia Artificial / Aprendizaje Automático, Big Data (datos masivos), Software
Experiencia laboral
2-4 años
Management
I've had experience in managing 1-5 people
Habilidades
Natural Language Processing
Machine Learning
Deep Learning
Data Science
Python
Git
PyTorch
Keras
CI/CD
k8s
Docker
Data Analysis
CNN
Idiomas
English
Profesional
Job search preferences
Posición
Machine Learning Engineer
Tipo de trabajo
A tiempo completo
Ubicación
台灣台北, 台灣台南市, 美國加利福尼亞洛杉磯, 德國慕尼黑, 加拿大安大略多倫多
A distancia
Interesado en trabajar a distancia
Freelance
No.
Educación
Escuela
NCKU, Master Degree
Mayor
Computer Science
Imprimir
User 9593 1475392706

Kai-Chou, Yang

As a Kaggle Competition Master and a winner of international data science challenges, I am experienced in machine learning, deep learning and related frameworks such as PyTorch.


My research focuses on natural language processing (NLP), where I have released 11 open-source projects such as MianBot (700+★ on Github) and presented certain academic papers on top conferences like ACL, AAAI, CIKM, and WSDM.

International Awards

For the following achievements, I am the first author as well as the team leader.

2nd Place, CIKM Cup: Cross-lingual Short-text Matching Challenge

  • Proposed two densely-connected architectures, CPRNN and DACNN, for sentence pair modeling.
  • Fused semantic features from different levels to create diversity intra-models.
  • The solution has been oral presented on CIKM 2018 in Turin, Italy.

3rd Place, WSDM Cup: Fake News Classification Challenge

  • Implemented various NLI networks like ESIM and injected world knowledge using BERT.
  • Proposed a disagreement-aware model based on the single-word attention.
  • The paper has been oral presented on WSDM 2019 in Melbourne, Australia.

4th place, Google AI: Gendered Pronoun Resolution Competition

  • Leveraged the information redundancy from BERT and extracted features from the optimal layer.
  • Proposed a multi-heads Siamese semantic scorer for answer selection.
  • The paper has been presented on ACL 2019 in Florence, Italy.

Kaggle Competition Master, Ranked top 0.2% (233/114,366)

  • Top 1% (4/838), Gendered Pronoun Resolution Competition.
  • Top 1% (27/4,550), Toxic Comment Classification Challenge.
  • Top 3% (30/1,449), CareerCon 2019 - Help Navigate Robots.
  • Top 4% (103/3,165), Jigsaw Unintended Bias in Toxicity Classification.
  • Top 6% (223/3,633), CommonLit Readability Prize. 
  • Top 10% (384/3,946), TalkingData AdTracking Fraud Detection Challenge.

Work Experience

Taiwan AI Labs, Machine Learning Engineer, Sep 2019 ~ Now

Question Answering System

  • Propose a conditional question generator with mT5 for controllable QA data augmentation and as the base of dense retrieval, which improves recall@50 from baseline model by 16%.
  • Build a generative pseudo labeling pipeline using a open-domain passage retriever and machine reader, which improve the nDCG@10 by 4.2 - 9.7, on various domains.
  • Build an efficient passage re-ranker based on tiny-bert with a time-series based clustering framework for effective negative passage sampling.
  • Leverage FinBERT on QA analysis and slot filling for fintech dialogue system.

Natural Language Understanding 

  • Implement a document encoder with self-contrastive learning and a document clustering algorithm, which is scalable for million scale of streaming data.
  • Implement a GROVER-like generator as the backbone for topic detection, article rewriting, and tag generation.
  • Propose a semi-automatic framework for fake-news identification, which gathers evidence from event properties, user behavior and textual features.
  • Propose a SOTA Chinese typo correction system based on a boosting loop of automatic speech recognition and text to speech for weak supervision.
  • Build a general-purpose NLP training pipeline for team use involving data augmentation, data regularization, and unsupervised domain adaptation.

Education

Master in Department of Computer Science, NCKU                                         GPA: 4.30

  • Honorary member of the Phi Tau Phi Scholastic Honor Society. (Ranked 1st among all graduates.)
  • As a teaching assistant for Introduction to Data Science, Data Mining and Discrete Mathematics.
  • As a speaker / teaching assistant for introduction lectures of machine learning.

Bachelor in Department of Computer Science, NCKU                                      GPA: 3.92






  • Academic excellence awards 2016.
  • Academic excellence awards 2015.
  • Honorable mention on the graduation exhibition.
  • Research assistant on a question answering system project for the Ministry of Science and Technology.

Side Projects

I list some of my project experiences. You can refer to my Github for the other interesting ideas.

Mianbot

  • Got 700+ stars and 200+ forks on Github.
  • Implemented the hierarchical keywords matching using word2vec.
  • Implemented the IR-based searching module to support chit-chat.
  • Allow user to define customized scenarios with JSON.
  • The extracted QA pairs were released in PTT-Gossiping-Dataset, a widely-used Chinese chit-chat corpus.
Paragraph image 00 00@2x

NCKU Smart-Life LineBot

  • A Linebot that helps solve trivial matters such as restaurant recommendation.
  • The dialogue system is based on LUIS for intent classification.
  • The backend was built with Django / Flask (new version) and host on Heroku.
  • The backend is connected with Line server using the web API.
Paragraph image 00 00@2x

Knowledge & Skills


  • General Machine Learning
    • Classification, Regression, Clustering, Boosting, Feature Engineering.
  • Natural Language Processing
    • Sentence Pair Modeling: Natural language Inference, Machine Reading Comprehension, Sentence Similarity
    • Text Classification / Regression / Clustering
    • Deep contextual representation (ELMO / BERT / XLNet / ELECTRA / RoBERTa / ERINE2.0 / BigBird / T5)
  • Recommendation System
    • Factorization: Matrix Factorization, Factorization Machine, DeepFM
    • Graph Embedding: DeepWalk, Node2Vec, item2Vec

Publication


  1. Fake News Detection as Natural Language Inference. Kai-Chou Yang; Timothy Niven; Hung-Yu Kao. WSDM Cup 2019
  2. Fill the GAP: Exploiting BERT for Pronoun Resolution. Kai-Chou Yang; Timothy Niven; Tzu Hsuan Chou; Hung-Yu Kao. ACLWS'19
  3. Generalize Sentence Representation with Self-Inference. Kai-Chou Yang; Hung-Yu Kao. AAAI 2020
  4. The Prevalence and Impact of Fake News on COVID-19 Vaccination in Taiwan: A Retrospective Study of Digital Media. Yen-Pin Chen; Yi-Ying Chen; Kai-Chou Yang; Feipei Lai; Chien-Hua Huang; Yun-Nung Chen; Yi-Chin Tu. JMIR
Resume
Perfil
User 9593 1475392706

Kai-Chou, Yang

As a Kaggle Competition Master and a winner of international data science challenges, I am experienced in machine learning, deep learning and related frameworks such as PyTorch.


My research focuses on natural language processing (NLP), where I have released 11 open-source projects such as MianBot (700+★ on Github) and presented certain academic papers on top conferences like ACL, AAAI, CIKM, and WSDM.

International Awards

For the following achievements, I am the first author as well as the team leader.

2nd Place, CIKM Cup: Cross-lingual Short-text Matching Challenge

  • Proposed two densely-connected architectures, CPRNN and DACNN, for sentence pair modeling.
  • Fused semantic features from different levels to create diversity intra-models.
  • The solution has been oral presented on CIKM 2018 in Turin, Italy.

3rd Place, WSDM Cup: Fake News Classification Challenge

  • Implemented various NLI networks like ESIM and injected world knowledge using BERT.
  • Proposed a disagreement-aware model based on the single-word attention.
  • The paper has been oral presented on WSDM 2019 in Melbourne, Australia.

4th place, Google AI: Gendered Pronoun Resolution Competition

  • Leveraged the information redundancy from BERT and extracted features from the optimal layer.
  • Proposed a multi-heads Siamese semantic scorer for answer selection.
  • The paper has been presented on ACL 2019 in Florence, Italy.

Kaggle Competition Master, Ranked top 0.2% (233/114,366)

  • Top 1% (4/838), Gendered Pronoun Resolution Competition.
  • Top 1% (27/4,550), Toxic Comment Classification Challenge.
  • Top 3% (30/1,449), CareerCon 2019 - Help Navigate Robots.
  • Top 4% (103/3,165), Jigsaw Unintended Bias in Toxicity Classification.
  • Top 6% (223/3,633), CommonLit Readability Prize. 
  • Top 10% (384/3,946), TalkingData AdTracking Fraud Detection Challenge.

Work Experience

Taiwan AI Labs, Machine Learning Engineer, Sep 2019 ~ Now

Question Answering System

  • Propose a conditional question generator with mT5 for controllable QA data augmentation and as the base of dense retrieval, which improves recall@50 from baseline model by 16%.
  • Build a generative pseudo labeling pipeline using a open-domain passage retriever and machine reader, which improve the nDCG@10 by 4.2 - 9.7, on various domains.
  • Build an efficient passage re-ranker based on tiny-bert with a time-series based clustering framework for effective negative passage sampling.
  • Leverage FinBERT on QA analysis and slot filling for fintech dialogue system.

Natural Language Understanding 

  • Implement a document encoder with self-contrastive learning and a document clustering algorithm, which is scalable for million scale of streaming data.
  • Implement a GROVER-like generator as the backbone for topic detection, article rewriting, and tag generation.
  • Propose a semi-automatic framework for fake-news identification, which gathers evidence from event properties, user behavior and textual features.
  • Propose a SOTA Chinese typo correction system based on a boosting loop of automatic speech recognition and text to speech for weak supervision.
  • Build a general-purpose NLP training pipeline for team use involving data augmentation, data regularization, and unsupervised domain adaptation.

Education

Master in Department of Computer Science, NCKU                                         GPA: 4.30

  • Honorary member of the Phi Tau Phi Scholastic Honor Society. (Ranked 1st among all graduates.)
  • As a teaching assistant for Introduction to Data Science, Data Mining and Discrete Mathematics.
  • As a speaker / teaching assistant for introduction lectures of machine learning.

Bachelor in Department of Computer Science, NCKU                                      GPA: 3.92






  • Academic excellence awards 2016.
  • Academic excellence awards 2015.
  • Honorable mention on the graduation exhibition.
  • Research assistant on a question answering system project for the Ministry of Science and Technology.

Side Projects

I list some of my project experiences. You can refer to my Github for the other interesting ideas.

Mianbot

  • Got 700+ stars and 200+ forks on Github.
  • Implemented the hierarchical keywords matching using word2vec.
  • Implemented the IR-based searching module to support chit-chat.
  • Allow user to define customized scenarios with JSON.
  • The extracted QA pairs were released in PTT-Gossiping-Dataset, a widely-used Chinese chit-chat corpus.
Paragraph image 00 00@2x

NCKU Smart-Life LineBot

  • A Linebot that helps solve trivial matters such as restaurant recommendation.
  • The dialogue system is based on LUIS for intent classification.
  • The backend was built with Django / Flask (new version) and host on Heroku.
  • The backend is connected with Line server using the web API.
Paragraph image 00 00@2x

Knowledge & Skills


  • General Machine Learning
    • Classification, Regression, Clustering, Boosting, Feature Engineering.
  • Natural Language Processing
    • Sentence Pair Modeling: Natural language Inference, Machine Reading Comprehension, Sentence Similarity
    • Text Classification / Regression / Clustering
    • Deep contextual representation (ELMO / BERT / XLNet / ELECTRA / RoBERTa / ERINE2.0 / BigBird / T5)
  • Recommendation System
    • Factorization: Matrix Factorization, Factorization Machine, DeepFM
    • Graph Embedding: DeepWalk, Node2Vec, item2Vec

Publication


  1. Fake News Detection as Natural Language Inference. Kai-Chou Yang; Timothy Niven; Hung-Yu Kao. WSDM Cup 2019
  2. Fill the GAP: Exploiting BERT for Pronoun Resolution. Kai-Chou Yang; Timothy Niven; Tzu Hsuan Chou; Hung-Yu Kao. ACLWS'19
  3. Generalize Sentence Representation with Self-Inference. Kai-Chou Yang; Hung-Yu Kao. AAAI 2020
  4. The Prevalence and Impact of Fake News on COVID-19 Vaccination in Taiwan: A Retrospective Study of Digital Media. Yen-Pin Chen; Yi-Ying Chen; Kai-Chou Yang; Feipei Lai; Chien-Hua Huang; Yun-Nung Chen; Yi-Chin Tu. JMIR