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4-6 years
6-10 years
10-15 years
More than 15 years
United States
智慧製造全端開發工程師 @聯華電子股份有限公司2022 ~ Present
・
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、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within one month
潘揚燊 ㄕㄣ Shen Pan Kaohsiung City，Taiwan • [email protected] 希望職務：人工智慧、機器視覺應用開發工程師 現任 : 聯華電子 RPA 平台全端開發工程師 您好，我是潘揚燊，目前任職於 聯華電子 ， 擔任 智慧製造 全端開發工程師 ， 畢業於元智大學工業工程與管理學系研
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
元智大學
・
工業工程與管理學系所
AI Engineer @Playsee2022 ~ Present
・
資料分析師、資料科學家、產品經理
Within one month
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
Employed
・
Ready to interview
Full-time / Interested in working remotely
4-6 years
National Cheng Kung University
・
心理所（認知科學所）
Postdoctoral Researcher @國立臺北科技大學(National Taipei University of Technology, Taipei Tech)2024 ~ Present
・
Researcher
Within one month
Employed
・
Open to opportunities
Part-time / Interested in working remotely
6-10 years
National Taipei University of Technology
・
Electrical Engineering and Computer Science
Senior Specialist Consultant @HSBC Software Dev(GD) Ltd.2021 ~ Present
・
Software Manager
Within two months
CHUNG-LIANG PAN Over 10 years software develop experience which including embedded system, cloud service platform building(data collect and analyse, commercial platform, photo recognised ) and apps developing. Currently i am leading a software team in to build and running a global finance system which handle huge amount of trades and settlements. Senior Specialist Consultant Guangzhou, 廣東省 China [email protected] Mobile:Skills Languages & Frameworks Experience in java,C ,C++,Python, Bash,Javascript,html,css Front-end Frameworks : Bootstrap,DirectFB,FFmpeg, OpenGL,Canvas Back-end Frameworks : SpringCloud,Jersey,Tomcat,nginx, swagger,vert
Employed
・
Open to opportunities
Full-time / Interested in working remotely
10-15 years
National Taiwan Ocen University
・
Computer Science
Senior Machine Learning Engineer @CoolSo2020 ~ Present
・
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
Within one month
vision for efficient counterfeit detection, safeguarding customer interests Leadership and Strategic Contributions - Founded and led a dynamic engineering team to develop counterfeit detection solutions, successfully showcased the prototype to customers within 3 months - Engaged with customers and investors to secure key partnerships and funding, secured $600,000 USD angel investment round with other founders - Fostered cross-departmental collaboration by working with product, sales and business development members to align priorities and strategies Technical Achievement and Innovations - Designed and trained deep learning models for counterfeit detection system through object detection and anomaly detection techniques - Deployed and integrated d...
Full-time / Interested in working remotely
4-6 years
University of California, Berkeley
・
Business/Commerce, General
Senior Technical Lead @Cisco2021 ~ 2024
・
Full-stack developer, Mobile developer
Within one month
in regional events that contribute to 10% of new users. Implement Scrum. Improve team productivity by 30%. Deliver on-demand features that yield 100% revenue growth. Senior Engineer Taiwan Mobile Co., Ltd. DecFeb 2015 iOS Developer AXIM Communications, Inc. DecAug 2012 Education University of California, San Diego M. E. Electrical Engineering SepJun 2008 University of Illinois at Urbana-Champaign B. S. Electrical Engineering SepDec 2005 Certificates Neural Networks and Deep Learning Coursera Dec 2023 Neural Networks Regularization and Optimization Coursera Jan 2024 Skills Frontend React, An...
Employed
Full-time / Interested in working remotely
10-15 years
University of California San Diego
・
Electrical Engineering全端工程師 @重量科技 KryptoGO2023 ~ Present
・
Senior Full Stack Developer/Engineering Manager
Within one month
Employed
・
Not open to opportunities
Full-time / Interested in working remotely
6-10 years
台灣大學
・
Computer Science and Information Engineering
Software Engineer @SoftLeader 松凌科技2022 ~ Present
・
Software Engineer / Backend Engineer
Within one month
ShengJu Wu(吳昇儒) Backend Engineer / Software Engineer • New Taipei City，TW • [email protected] Skills Programming Java JavaScript C/C++ Python SQL Web/Framework Spring Boot/SpringFrameWork PostgreSQL, Redis Embedded System SSD development FTL design Professional Skills Computer Vision Image Processing Machine Learning Language Chinese: Native language English: TOEIC CertificateCertificate Fundamentals of Deep Learning for Computer Vision - NVIDIA Deep Learning Institute (2019/6) Work Experience SoftLeader Technology Corp, Software Engineer, Septo now. R&D engineer: 1. Engaged in FileUpload system and ETL for clients. 2.
Employed
・
Not open to opportunities
Full-time / Interested in working remotely
4-6 years
National Taiwan Normal University
・
Electrical Engineering
工程師 @永豐金證券2018 ~ Present
・
Python Developer, Rust Developer, BigData Engineer
Within one year
幫我們輸入驗證碼，準時在12點整搶票不必擔心忘記搶票回不了學校或回不了家，當時apple還沒推出coreML可以輕易的將python的deep learning model轉換成ios可執行。 由於台鐵法規關係，這個專案目前已經不公開。 Talks 花蓮Py 2016 Use deep learning to hack captcha MLDM Mondy Training the agent for trading use Interactive Broker
Employed
Full-time / Interested in working remotely
4-6 years
國立東華大學 | National Dong Hwa University
・
Arts and Creative IndustriesSoftware Engineer @Vertiv Taiwan2021 ~ Present
・
Backend Engineer, Data Engineer
Within one month
Employed
Full-time / Interested in working remotely
6-10 years
TamKang University
・
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Adaptability
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Communication
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Time Management
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Teamwork
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Leadership
Ability to coach, guide, and inspire a team to achieve a shared goal or outcome effectively.
Professional Background
Current status
Employed
Job Search Progress
Not open to opportunities
Professions
Machine Learning Engineer, Data Scientist
Fields of Employment
Artificial Intelligence / Machine Learning, Big Data, Software
Work experience
2-4 years
Management
I've had experience in managing 1-5 people
Skills
Languages
English
・
Professional
Job search preferences
Positions
Machine Learning Engineer
Job types
Full-time
Locations
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
Remote
Interested in working remotely
Freelance
No
Educations
School
NCKU, Master Degree
Major
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