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De 4 a 6 años
6-10 años
10-15 años
Más de 15 años
Tainan City, Taiwan
Technical Project Manager/技術專案管理 @CM Visual Technology Corporation/微采視像科技股份有限公司2016 ~ 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 Engineer、Deep Learning Engineer、Data Scientist
Más de un año
data science. Accustomed to communicating and failure analyzing with cross department. Tainan City, Taiwan Skill Experience 5yrs Product development and validation 3yrs FAE to client 3yrs Display development Optic Display optics and design Wide-view technology Polarizer and Thin film process Knowledge of Color theory, Optic, Crystal optic Data science Statistic Python, R, SQL DFSS Knowledge of ML/DL, Data modeling and visualization Personality Traits Motivated learner Accustomed to communicating Flexible and open-mind Language Chinese - Native English - Intermediate Work Experience Technical Project Manager CM Visual Technology Corporation •Present Responsible for: 1. New product development project
Empleado
A tiempo completo / Interesado en trabajar a distancia
6-10 años
National Sun Yat-Sen University/國立中山大學
・
Optoelectronic Engineering/光電工程
Senior Product Manager @Kdan Mobile2022 ~ Presente
・
Product Management
En un mes
Empleado
・
Abierto a oportunidades
A tiempo completo / Interesado en trabajar a distancia
6-10 años
HHL LEIPZIG GRADUATE SCHOOL OF MANAGEMENT – Top 100 Global MBA by The Economist
・
Management, Entrepreneurship, Strategy
資深經理 @緯創資通2021 ~ Presente
・
Technical Manager
En seis meses
National Taiwan University of Science and Technology - Master of Information Engineering Experience: 2010 Wistron - Software Engineer 2015 Wistron - ML/DL Image Processing Engineer 2019 Wistron - Technical Manager 2020 MIT - Computer Science and Artificial Intelligence Laboratory (CSAIL) Visiting Engineer Competition: 2016 Ministry of Economic Affairs Bureau of Industry – Mastering the Data Context Hackathon Competition, Data Marketing Award 2017 Kaggle: The Nature Conservancy Fisheries Monitoring – bronze medal <6% 2018 Wistron Capital Entrepreneurship Competition 3rd place - Baby Guardian In 2020, I was fortunate to be a Visiting Engineer at Massachusetts Institute of Technology-Computer Science & Artificial Intelligence Laboratory for six months, to
Empleado
A tiempo completo / Interesado en trabajar a distancia
10-15 años
National Taiwan University of Science and Technology
・
Master's degree Computer Science and Information EngineeringEmpleado
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
University of Michigan(Coursera)
・
Using Python to Access Web Data
半導體研發工程師 @ UMC2015 ~ Presente
・
En un plazo de tres meses
20% to almost zero by optimizing plasma uniformity in ULK deposition. Troubleshooting in dielectric process for 14 nm and 22 nm mass product. Optimized ULK film for 28 nm shrinkage to 22 nm technology. Developed high compressive TEOS for wafer bonding. ( < -350 MPa) Developed Ar carrier gas in TEOS deposition for helium reduction. Education History National Tsing Hua University (NTHU), Taiwan,Ｍaster of Science in Chemistry National Kaohsiung Normal University, Taiwan,Bachelor of Science in Chemistry Skill Specializing in ULK/TEOS/ALD processes. Experience with LAM and AMAT t...
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
清華大學
・
化學Sr. UX Researcher @17LIVE2021 ~ Presente
・
UX Designer, User Researcher
En seis meses
Empleado
・
No está abierto a oportunidades
A tiempo completo / Interesado en trabajar a distancia
6-10 años
國立清華大學
・
社會學, 哲學
缺陷分析工程師 @TSMC2014 ~ 2017
・
資料科學家/機器學習工程師
Más de un año
problems, familiar with the way that defect is discovered and the mechanism of defect formation. Also experienced on develop defect analysis system with IT and machine learning engineer. For job skills/tools, learned to program by VBA, SQL and some python because of the large amount of data analysis at work, and also try to apply machine learning to work. Currently working and studying hard to become a data scientist. 資料科學家/機器學習工程師 Taipei Special Municipality，TW [email protected] 工作經
A tiempo completo / Interesado en trabajar a distancia
De 4 a 6 años
清華大學
・
物理系El plan de reclutamiento más ligero y eficaz
Busque currículums y tome la iniciativa de ponerse en contacto con los solicitantes de empleo para lograr una mayor eficacia en la contratación. La elección de cientos de empresas.
- Examinar todos los resultados de la búsqueda
- Acceso ilimitado para iniciar nuevas conversaciones
- currículos accesibles sólo para empresas de pago
- Ver dirección de correo electrónico y números de teléfono de los usuarios
Consejos de búsqueda
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Search a precise keyword combination
senior backend php
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UI designer -UX
Sólo los currículums públicos están disponibles con el plan gratuito.
Actualiza a un plan avanzado para ver todos los resultados de la búsqueda incluyendo decenas de miles de currículums exclusivos en CakeResume.
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
Ability to prioritize tasks based on importance; and have them completed within the assigned timeline.
Teamwork
Ability to work cooperatively, communicate effectively, and anticipate each other's demands, resulting in coordinated collective action.
Leadership
Ability to coach, guide, and inspire a team to achieve a shared goal or outcome effectively.
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
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
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.
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.
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
- Fake News Detection as Natural Language Inference. Kai-Chou Yang; Timothy Niven; Hung-Yu Kao. WSDM Cup 2019
- Fill the GAP: Exploiting BERT for Pronoun Resolution. Kai-Chou Yang; Timothy Niven; Tzu Hsuan Chou; Hung-Yu Kao. ACLWS'19
- Generalize Sentence Representation with Self-Inference. Kai-Chou Yang; Hung-Yu Kao. AAAI 2020
- 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
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.
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.
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
- Fake News Detection as Natural Language Inference. Kai-Chou Yang; Timothy Niven; Hung-Yu Kao. WSDM Cup 2019
- Fill the GAP: Exploiting BERT for Pronoun Resolution. Kai-Chou Yang; Timothy Niven; Tzu Hsuan Chou; Hung-Yu Kao. ACLWS'19
- Generalize Sentence Representation with Self-Inference. Kai-Chou Yang; Hung-Yu Kao. AAAI 2020
- 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