Noppayut Sriwatanasakdi
Software Engineer at Astellas Pharma
Chiyoda, Japan
Summary
👤
Senior🎓
Top SchoolNoppayut Sriwatanasakdi is a software engineer with 11 years of experience specializing in machine learning, data mining, and natural language processing, currently based in Chiyoda, Japan. He holds a Master's in Artificial Intelligence from Osaka University and a Computer Engineering degree from Chulalongkorn University, and his thesis focused on mining data in dynamically changing environments. Noppayut has moved between research and industry roles—ranging from R&D and data science to NLP engineering at SQUARE ENIX AI & ARTS and Astellas Pharma—delivering production-ready models and cross-functional data solutions. He contributes to open-source Thai NLP (PyThaiNLP) by improving tokenization and numeric handling, a practical detail that reflects his attention to real-world language data quirks. Colleagues rely on him to bridge research insights and engineering rigor to improve chatbots, text analytics, and predictive telemetry systems.
11 years of coding experience
8 years of employment as a software developer
Master's degree, Artificial Intelligence, Master's degree, Artificial Intelligence at Osaka UniversityBachelor's degree, Computer Engineering, 3.78/4.00, Bachelor's degree, Computer Engineering, 3.78/4.00 at Chulalongkorn University
Japanese, Thai, English
Github Skills (7)
unit-testing10
nlp10
nlpjs10
python10
natural-language-processing10
text-processing10
pytest9
Programming languages (2)
Github contributions (5)
PyThaiNLP/pythainlp
Oct 2022 - Oct 2022
Thai natural language processing in Python
Role in this project:
Back-end Developer & QA Engineer
Back-end Developer & QA EngineerContributions:29 commits, 4 PRs, 9 comments in 20 days
Contributions summary:Noppayut primarily contributed to the back-end functionality of the Thai natural language processing library. Their work focused on improving the word tokenizer by integrating a numeric format postprocessor, ensuring proper handling of numerical data formats. They also added unit tests to validate the correct behavior of the tokenizer and address identified issues. Furthermore, the user added functionality for enhanced tokenization by allowing users to join broken numerical formats.
nlpword-segmentationpythonthai-nlp-librarylanguage-processing
noppayut/noppayut.github.io
Feb 2022 - Nov 2024
A beautiful, simple, clean, and responsive Jekyll theme for academics
Contributions:11 PRs, 22 pushes, 12 branches in 2 years 9 months
responsive-jekyll-themeacademicscleanjekylljekyll-theme
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