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On
4〜6年
6〜10年
10〜15年
15年以上
Past
Service Provider @Taron Solutions Limited2023 ~ 2023
・
AI工程師、機器學習工程師、電腦視覺工程師、資料科學家、Machine Learning Engineer、Computer Vision Engineer、Data Scientist
1ヶ月以内
轉為簡體，最終使用情感分析工具(snownlp)進行股市漲跌分析。 技術：NLP、Beautifulsoup、 opencc 、 snownlp 、 Matplotlib 台灣景氣指標預測模型 side project 使用深度學習框架(Pytorch)自行搭建預測模型，以各式台灣景氣指標當作輸入，輸出未來經濟景氣趨勢階段。 技術：Pytorch、Pandas、Numpy、 Sklearn 論文發表 • Chen, X. Z., Li
無職
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
國立臺北科技大學
・
資訊工程
Algorithm Research & Development @適着三維科技股份有限公司 TG3D Studio Inc.2021 ~ 現在
・
Software Engineer
1ヶ月以内
就職中
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
國立台灣大學
・
生物產業機電工程所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
1ヶ月以内
就職中
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
國立政治大學（National Chengchi University）
・
資訊科學系Past
博士後研究員 @洛桑大學神經發育疾病實驗室2023 ~ 2023
・
Data Scientist, Data Analyst, Machine Learning Engineer
1ヶ月以内
無職
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
洛桑聯邦理工學院(EPFL)
・
神經科學
智慧製造全端開發工程師 @聯華電子股份有限公司2022 ~ 現在
・
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
1ヶ月以内
用機器及降低故障率。 生產設備數據分析，製程問題進行分析，檢視錯誤原因，如: 負擔過重、溫度過高等。 Skills Python Langchain Numpy OpenCV Tensorflow (tf.keras) Pytorch Scikit-learn C# EmguCV ASP.NET Windows Forms 程式設計開發、單元測試專案 Halcon 影像處理 影像定位 瑕疵判斷 物件量測 Skills Database MySQL Oracle ArangoDB LLM Tool:langchain Vector DB
就職中
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
元智大學 Yuan Ze University
・
工業工程與管理學系所
Data Engineer @TSMC 台積電2022 ~ 現在
・
資料分析師、演算法工程師、軟體工程師、軟體專案管理
1ヶ月以内
various database. establish a CI/CD pipeline to kubernetes for the inner platform to imporving the seculity and stable of the process. NLP Engineer,–, Ubestream. I Led and designed a chatbot service project in EC, using Django and MongoDB. To develop NLU services with Huggingface, PyTorch, and Keras, including intent classification, NER, etc. At the same time, led a junior engineer team to set and complete the tasks, team members including 18 interns and 4 full-time engineers. And I help to prepare the product demo encompassing internal sharing, investor fundraising, and international
就職中
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
國立中央大學 National Central University
・
網路學習科技研究所
AI Engineer @Playsee2022 ~ 現在
・
資料分析師、資料科學家、產品經理
1ヶ月以内
李昀庭 Data scientist Taiwan 技能 Machine learning and Engineering skills: Python, Big Query, Google Storage, Linux, Docker, GCP, AWS, Scikit-learn, Tensorflow, Pytorch, MLOps, FastAPI, Machine Learning, Deep Learning, Computer Vision, NLP Experimental design, Project management, Product design English - TOEIC 725 工作經歷 AI工程師 Playsee NovPresent Taipei, Taiwan 自動化標註推薦系統 設計並實踐架構取代25個標註者並及時標記和篩選視頻審核內容。 設計並優化影片
就職中
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
National Cheng Kung University
・
心理所（認知科學所）
Past
Senior Firmware Engineer @Artesyn Embedded Technologies2019 ~ 2022
・
韌體工程師/軟體工程師/控制工程師/演算法工程師/
1ヶ月以内
Ted Li Senior Firmware Engineer Over 6 years of firmware/software development expertise as a Senior Firmware Engineer, specializing in embedded systems, cross- functional projects, and RL-optimizations. Driving global technical innovations and training. New Taipei City, Taiwan [email protected] https://github.com/armcortex https://www.linkedin.com/in/ted-li/ https://about.armcortex.cc/ Skill Programming C/C++ Python Bash SQL AI (PyTorch, TensorFlow, Keras) Tool RTOS Embedded System Git Docker/Docker Compose
無職
・
面接の用意ができています
フルタイム / リモートワークに興味あり
6〜10年
日本電氣通信大學 The University of Electro-Communications (UEC)
・
Robotics Engineering
全端工程師 @中冠資訊股份有限公司2021 ~ 現在
・
網站後端工程師
1ヶ月以内
喬康豪 full-stack-engineer 前端技能 : vue.js, angular, sass, restful api, websocket 後端技能 : node.js, spring boot, , rabbitmq, websocket, k8s 工作經歷： full-stack-engineer: 3~4年 Fontend-engineer： 2~3年 Deep-learning engineer： 2~3年 Android app developer： 1年 email： [email protected] Skliis Font-End Vue.js angular Sass websocket RWD Back-End spring boot rabbitmq websocket Restful Api nodejs laravel Deep-Learning Object Detection Object Tracking YOLO pytorch 開發工具及環境 git docker k8s
就職中
・
面接の用意ができています
フルタイム / リモートワークに興味あり
6〜10年
清華大學 National Tsing Hua University
・
核子工程 nuclear engineering
Past
Lead Data Scientist / Senior Data Scientist @Vinnovation Network 維諾森資訊科技2022 ~ 2023
・
資料科學家、資料科學工程師、機器學習工程師
1ヶ月以内
Shih-Wen Tsou - With more than 5 years of experience in Data Analysis, Machine Learning and Deep Learning, familiar with Modeling, Data Analysis, Image Processing, Machine Learning, and Deep Learning. Taipei City, Taiwan WORK EXPERIENCE Lead Data Scientist / Full Stack Data Scientist, Vinnovation Network, Taipei, Taiwan Data Engineering / Data Analysis Spearheaded the development of a fully automated data integration pipeline that aggregated diverse data sets into a S3 Data Lake. Successfully integrated a range of data sources, including real-time data feeds from AWS Redshift and DocumentDB, as well as batch processes to import traditional CSV
無職
・
面接の用意ができています
フルタイム / リモートワークに興味あり
4〜6年
台灣大學
・
大氣科學所最も簡単で効果的な採用プラン
80万枚以上の履歴書を検索して、率先して求人応募者と連絡をとって採用効率を高めましょう。何百もの企業に選ばれています。
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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
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
現在の状況
就職中
求人検索の進捗
就職を希望していません
Professions
Machine Learning Engineer, Data Scientist
Fields of Employment
人工知能／機械学習, ビッグデータ, ソフトウェア
職務経験
2〜4年
Management
I've had experience in managing 1-5 people
スキル
言語
English
・
ビジネスレベル
Job search preferences
希望のポジション
Machine Learning Engineer
求人タイプ
フルタイム
希望の勤務地
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
リモートワーク
リモートワークに興味あり
Freelance
いいえ。
学歴
学校
NCKU, Master Degree
専攻
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