Taisei Klasen
Full Stack Engineer at COTEN INC
Tokyo, Japan
Summary
👤
Senior🎓
Top SchoolTaisei Klasen is a Full Stack Engineer based in Tokyo with nine years of experience building cloud-native and front-end infrastructure at scale. He spent several years at Google contributing to Compute front-end systems and later to Google Cloud Explainable AI, where he integrated feature attribution capabilities into Vertex AI's Python SDK and LIT integration for TensorFlow models. Now at COTEN INC, he applies both UI/infra and ML interpretability experience to deliver practical, user-focused systems. Taisei combines hands-on coding across the stack with a strong orientation toward usability and explainability in ML—an often overlooked but crucial bridge between models and product teams. He began his engineering path contributing to academic open-source ADT tooling and has intern and early-career experience that reinforces his pragmatic approach to software quality. Fluent in collaborative, cross-functional environments, he brings both production-grade engineering and research-informed ML tooling experience.
9 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at University of Oregon
Japanese, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (7)
vertex-ai10
xai10
machine-learning10
explainable-artificial-intelligence10
tensorflow10
python10
pandas9
Programming languages (4)
Github contributions (5)
googleapis/python-aiplatform
Dec 2021 - Mar 2022
A Python SDK for Vertex AI, a fully managed, end-to-end platform for data science and machine learning.
Role in this project:
ML Engineer
ML EngineerContributions:30 reviews, 6 commits, 9 PRs in 2 months
Contributions summary:Taisei contributed to the integration of the Explainable AI (XAI) SDK within the Vertex AI platform, adding feature attribution capabilities for TensorFlow models. They implemented methods for Pandas DataFrames and TensorFlow saved models within the LIT (Language Interpretability Tool) integration. The changes involved modifying the `lit.py` file to incorporate XAI SDK functionality and added code to the `_VertexLitModel` class to enable feature attribution for TensorFlow models within the LIT environment. Additional changes include fixes to improve usability.
pythonend-to-endsciencedata-sciencemachine-learning
taiseiak/python-aiplatform
Nov 2021 - Mar 2022
A Python SDK for Vertex AI, a fully managed, end-to-end platform for data science and machine learning.
Contributions:5 PRs, 62 pushes, 8 branches in 3 months
fairness-mlpythonend-to-endsciencedata-science
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