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智慧製造全端開發工程師 @聯華電子股份有限公司2022 ~ Hiện tại
・
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
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元智大學 Yuan Ze University
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工業工程與管理學系所AI Engineer @Playsee2022 ~ Hiện tại
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Sẵn sàng phỏng vấn
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4-6 năm
National Cheng Kung University
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心理所（認知科學所）
Principal @Cascade Data Labs2016 ~ 2022
・
Director Data
Trong vòng hai tháng
Emily Ledoux Delivery Principal Seasoned Delivery Principal in the Data Practice. Focused on designing robust, scalable data ecosystems in the cloud to feed insights and data visualizations. Well-rounded consultant with experience spanning sales, recruiting, and delivery. Proven Delivery & Client Lead. Portland, OR, USA https://www.linkedin.com/in/emily-ledoux/ Work Experience JanuaryPresent Principal Data Architect Kin + Carta Delivery or Client Lead for over 25 resources, including direct reports, delivery oversight, hours tracking, QBRs, onboarding management, budget ownership and related responsibilities. Cloud Architect, designing Azure and
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EconomicsSenior Machine Learning Engineer @CoolSo2020 ~ Hiện tại
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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 Engineer、Deep Learning Engineer、Data Scientist
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4-6 năm
University of California, Berkeley
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Business/Commerce, General
全端工程師 @重量科技 KryptoGO2023 ~ Hiện tại
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Senior Full Stack Developer/Engineering Manager
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Recognition System: A website system, integrated with deep learning models, helps police department deal with broken fingerprints matching. Impact Reduce the omission rate of broken fingerprints matching, which current matching systems do not perform well. Scope of Work: Built the website with ReactJS, NestJS, TypeORM, PostgreSQL, FastAPI, and Pytorch. Wrote necessary automated regression tests with Cypress, integrated with Gitlab CI, to enable rapid product iterations. Wrote deployment scripts using docker compose. Wrote Error Tracking with Sentry and logging with Winston. Automated Production Line for Hosiery Industry An ongoing project by the time this is
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台灣大學
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Computer Science and Information Engineering
工程師 @永豐金證券2018 ~ Hiện tại
・
Python Developer, Rust Developer, BigData Engineer
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作。 Education 國立東華大學 藝術創意產業學系Skills Python Numpy / Pandas / Polars Celery FastAPI Visualization Rust Tauri Poem Tokio Polars CICD Docker Docker-compose K8S Gitlab CI Github Action Deep Learning CNN / RNN / GNN Reinforcement Learning Tensorflow Pytorch Keras Other Language Rust javascript Swift C / C++ Dart Design Photoshop illustrator After Effects Cinema 4D 3D Modeling / Rendering Generative Design Side Project TradingGym more 這個專案啟發於openai的gym，gym是一個環境可以快速
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4-6 năm
國立東華大學 | National Dong Hwa University
・
Arts and Creative Industries
Research Engineer
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Intelligence From Taiwan Artificial Intelligence Academy 2021~2023 Patent Application TOPIC: A Robust Counting and Measurement Approach for Stacked Substrates Patents of of this work are approval by Taiwan Intellectual Property Office, Invention patentwas accepted in 30 Mar 2023, Utility patent ( Mwas accepted in AugOpenCV Official Training DEEP LEARNING WITH PYTORCH Focus on deep learning 2020 OpenCV Official Training COMPUTER VISION 2 Especially focus on face recognition and plate recognition 2020 Publish conference paper in the CVGIP 2020 TOPIC: A VISION-BASED PITCHER RELEASE POINT DETECTION SYSTEM, Hoster : NCTU, NTHU, and IPPR 2019 OpenCV Official Training COMPUTER VISION 1 Especially
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4-6 năm
National Chiao Tung University
・
Computer Science
AI Engineer @Revlis Biotech Co. Ltd., Yunlin County, Taiwan2022 ~ Hiện tại
・
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
Trong vòng hai tháng
in 8 years. Coordinated with Environment and Construction Authority to proceed monitoring projects. EducationMaster of Science National Sun Yat-Sen University Biological Oceanography, Multivariate Analysis, Time Series AnalysisBachelor of Science National Sun Yat-Sen University Oceanography Skills Certificate Deep Learning Machine Learning Statistics Multivariant Analysis Python SPSS SAS PyTorch Tensorflow/Keras Scikit-Learn Matplotlib Seaborn 1. Python from the Beginning / Udemy 2. Python A-Z / Udemy 3. Machine Learning A-Z / Udemy 4. Deep Learning A-Z / Udemy 5. TensorFlow 2.0 using Keras API / Udemy
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Full-time / Quan tâm đến làm việc từ xa
10-15 năm
National Sun Yat-sen University
・
Biological Oceanography, Multivariate Analysis, Time Series Analysis 
Senior Machine Learning Engineer @C-Media Electronics2020 ~ 2021
・
Machine Learning Scientist, Data Scientist
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Hao-Chun (Chad) Yang Ph.D Ph.D Graduate @NTHU (EE) | Seeking AI/ML R&D Position | Speech, IOT, Health Informatics, Computational Neuroscience | pytorch, tensorflow Room 315, General Building III, No. 101, Section 2, Kuang-Fu Road,Hsinchu City, Taiwan Skills Programming Programming: Python, Matlab DevOps: AWS, GCP, Git, Docker Deep Learning: Pytorch, Tensorflow, Keras ML& Data Science: Sklearn, Numpy, Pandas, Matplotlib MLOps: MLflow, W&B Special HonorsBest Challenge Poster - Physionet/CINC ChallengeTravel Grants - IEEE SPS SocietyPresident Scholarship - NTHU Education National Tsing Hua University Ph.D. in Electrical Engineering (SepPresent) National Tsing
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Full-time / Quan tâm đến làm việc từ xa
4-6 năm
清華大學
・
電機工程
創辦人 @酷喬伊科技有限公司2020 ~ Hiện tại
・
Python developer
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間也碰壁被客戶打槍了許多次，但也了解到從研發到產品與服務並不是僅單一面向的東西，而是一連串的整合關係。 技能 PyTorch Python PostgreSQL MySQL SQLite3 JavaScript Flask FastAPI Django Azure App Service GCP Cloud SQL Redis Scrapy Selenium Web Crawler Docker Git Pandas Scikit-Learn 語言 Chinese — 母語或雙語 English — 中階 專案 Telegram Stock Price Bot 算是近期做的小專
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Fu Jen Catholic University
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Major, Optical Physics, Minor, Finance and international businessKế hoạch tuyển dụng đơn giản và hiệu quả nhất
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Tiến trình tìm việc
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Professions
Machine Learning Engineer, Data Scientist
Fields of Employment
Trí tuệ nhân tạo/ Máy học, Big Data, Phần mềm
Kinh nghiệm làm việc
2-4 năm
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I've had experience in managing 1-5 nhân viên
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Machine Learning Engineer
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Full-time
Địa điểm
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
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Quan tâm đến làm việc từ xa
Freelance
Không.
Học vấn
Trường học
NCKU, Master Degree
Chuyên ngành
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