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4-6 tahun
6-10 tahun
10-15 tahun
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Taipei, Taiwan
Avatar of 雷克魯.
Team Lead
Dalam satu tahun
台灣對接的法規,並且嘗試了解不同金流管道費率與優缺點,去提升專案最終完整度。 技能 Program PHP Laravel MySQL Memcache Redis Supervisor Host Host Architecture Ali AWS GCP Linode Management Lead team Scrum Water fall Scheduling Market survey 工作經歷 經歷一,2020 年 4 月 - NOW 海外棋牌遊戲公司 , 台灣, 台北, 技術部 team leader 1.PHP Laravel 5.7 與 Think PHP 5
PHP
Laravel Framework
MySQL
Tidak terbuka untuk peluang
Full-time / Tertarik bekerja jarak jauh
6-10 tahun
逢甲大學
資訊工程
Avatar of Gladys Wang.
Avatar of Gladys Wang.
Past
Specialist @MANPOWER
2016 ~ 2018
HR
Lebih dari satu tahun
Gladys (Wen-Ling) Wang  [email protected], Taiwan Work Experience Peloton Interactive Taiwan People Support Dec 2020 ~ SepProvide support on global on to offboarding life cycle process and related operation, improving and modifying global policies to fit into local procedure - In charge of all general People issues where required, acted as an cross functional communicator and active seeker to support business units to execute the management and concern - Build up various campaigns including Taiwan All Hands, birthday celebration, festival virtual family activities time; design and sourcing employee gifts. - Top down/ bottom up global projects including upgrading
Engagement
Compensation and Benefits Management
Human Resource Management
Tidak bekerja
Full-time / Tertarik bekerja jarak jauh
4-6 tahun
Shih Hsin University
Social Phycology

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Definition of Reputation Credits

Technical Skills
Specialized knowledge and expertise within the profession (e.g. familiar with SEO and use of related tools).
Problem-Solving
Ability to identify, analyze, and prepare solutions to problems.
Adaptability
Ability to navigate unexpected situations; and keep up with shifting priorities, projects, clients, and technology.
Communication
Ability to convey information effectively and is willing to give and receive feedback.
Time Management
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Leadership
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Dalam satu tahun
Machine Learning Engineer
Logo of Taiwan AI Labs.
Taiwan AI Labs
2019 ~ Sekarang
Taipei, 台灣
Latar Belakang Profesional
Status sekarang
Sudah bekerja
Tahap pencarian kerja
Tidak terbuka untuk peluang
Profesi
Machine Learning Engineer, Data Scientist
Bidang Pekerjaan
Intelegensi Artifisial/Pemelajaran Mesin, Big Data, Software
Pengalaman Kerja
2-4 tahun
Management
Saya berpengalaman mengelola 1-5 orang
Keterampilan
Natural Language Processing
Machine Learning
Deep Learning
Data Science
Python
Git
PyTorch
Keras
CI/CD
k8s
Docker
Data Analysis
CNN
Bahasa
English
Profesional
Preferensi Pencarian Pekerjaan
Jabatan
Machine Learning Engineer
Tipe Pekerjaan
Full-time
Lokasi
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
Bekerja jarak jauh
Tertarik bekerja jarak jauh
Freelance
Tidak
Pendidikan
Institusi Pendidikan
NCKU, Master Degree
Jurusan
Computer Science
Cetak
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
CV
Profil
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