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Avatar of Fatemeh Bahartash.
Avatar of Fatemeh Bahartash.
Radiologist and gynecologist @Taleqani Hospital of Tehran
2005 ~ Présent
Plus d'1 an
Bachelor's Of Radiology : MRI Expert & expert of OPG , Bitewing technique , Lateral cephalometry , Mammography, Bone density , Single tooth radiography , Color Radiography ,Visipek Enema Radiology , Swallow , Transit ,,Work experience at General Hospital, with orthopedic cases,In the field of cosmetics, a professional make-up artist; Specializing in providing a variety of makeup, Breeze Bros. eyebrow tattoo, eyebrow shadow , Journal Haircut , Hair Brushing , Hair color and lightSkills instagram Hair Cutting Radiology MRI Makeup Artistry tattoo Turkish English as a Second Language (ESL) Hair Coloring Hair Styling Art Beauty Makeup Supervisory Skills opg Languages Persian — Professional Turkish — Fluent Azerbaijani — Professional English — Fluent
instagram
Hair Cutting
Radiology
Temps plein / Je ne suis pas intéressé par le travail à distance
10 à 15 ans
Urmia University
Bachelor's Of Radiology : MRI Expert & expert of OPG , Bitewing technique , Lateral cephalometry , Mammography, Bone density , Single tooth radiography , Color Radiography ,Visipek Enema Radiology , Swallow , Transit ,, Work experience at General Hospital, with orthopedic cases, In the field of cosmetics, a professional make-up artist; Specializing in providing a variety of makeup, Breeze Bros. eyebrow tattoo, eyebrow shadow , Journal Haircut , Hair Brushing , Hair color and light .
Avatar of SJ   Hairdressing and makeup.
Avatar of SJ   Hairdressing and makeup.
hair and makeup artist @citygirl
hair and makeup artist
Plus d'1 an
work alongside other creatives within fashion, film and visual industries in addition to providing all types of hairdressing and makeup services both for private clients and at corporate events . hair and makeup artist GRE, GB [email protected] and Experience OctoberPresent London, Brighton , Home Counties, Ibiza Freelance Hair and Makeup Artist Presently completing my masters in fashion branding and marketing working with buying teams and head designers to obtain more knowledge of global branding and brand positioning. Managing a variety of hair and beauty services, including specialist cutting, colouring, styling, extensions, bridal hair, bridal makeup and
Word
Photoshop
Excel
Temps partiel / Intéressé par le travail à distance
Plus de 15 ans
University of Sothhampton
Fashion Marketing and Branding
Avatar of the user.
Marketing Manager
Dans 2 mois
Word
Illustrator
Photoshop
Employé
Ne recherche pas de nouvelles opportunités
Temps plein / Uniquement Travail à distance
Plus de 15 ans
The Australian National University
Visual Art
Avatar of the user.
Avatar of the user.
Research Analyst @MatrixDAO
2022 ~ Présent
Dans 6 mois
Google Drive
Employé
Temps plein / Uniquement Travail à distance
4 à 6 ans
Fju Jen Catholic University
Public Health, Japanese
Avatar of the user.
Avatar of the user.
Photographer @Har Kwan Luk
2000 ~ Présent
Photographer
Plus d'1 an
Photoshop
Photography
Employé
Intéressé par le travail à distance
Plus de 15 ans
Univeristy of Houston
Photography

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Dans 1 an
Machine Learning Engineer
Logo of Taiwan AI Labs.
Taiwan AI Labs
2019 ~ Présent
Taipei, 台灣
Professional Background
Statut Actuel
Employé
Progrès de la Recherche d'Emploi
Ne recherche pas de nouvelles opportunités
Professions
Machine Learning Engineer, Data Scientist
Fields of Employment
Intelligence Artificielle / Machine Learning, Big Data, Logiciel
Expérience Professionnelle
2 à 4 ans
Management
I've had experience in managing 1-5 people
Compétences
Natural Language Processing
Machine Learning
Deep Learning
Data Science
Python
Git
PyTorch
Keras
CI/CD
k8s
Docker
Data Analysis
CNN
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English
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Machine Learning Engineer
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Temps plein
Lieu Désiré
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
Travail à distance
Intéressé par le travail à distance
Freelance
Non.
Éducation
École
NCKU, Master Degree
Spécialisation
Computer Science
Imprimer
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
Profile
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