Yuichi Tateno
New Manufacturing Technology Lead (Digitalisation Lead)
United Kingdom
Summary
👤
Senior🎓
Top SchoolYuichi Tateno is a multidisciplinary technology leader with 20 years’ experience bridging pharmaceutical R&D, manufacturing and IT—currently leading New Manufacturing Technology and Digitalisation at AstraZeneca. He combines hands-on software and automation expertise with OT/cybersecurity leadership, having initiated R&D OT security at GSK and contributed test automation to prominent open-source projects like Fluentd. Yuichi excels at turning experimental pilots into enduring systems—delivering lab automation and Smart Manufacturing 2030 initiatives while balancing value, compliance (GMP) and risk. A Cambridge-trained scientist, he is equally comfortable mentoring engineers, influencing enterprise strategy, and shutting or pivoting projects when data indicate diminished value. His background reveals an uncommon mix of deep laboratory practice, practical coding/test automation, and enterprise cyber/innovation governance.
20 years of coding experience
16 years of employment as a software developer
Master of Science (MSc), (BA & MA) and PhD, Natural Sciences, Master of Science (MSc), (BA & MA) and PhD, Natural Sciences at University of Cambridge
Japanese
Github Skills (7)
testing10
fluentd10
test-automation10
ruby10
collector9
data-collection9
logging9
Programming languages (15)
Github contributions (5)
fluent/fluentd
Oct 2011 - Feb 2013
Fluentd: Unified Logging Layer (project under CNCF)
Role in this project:
QA Engineer / Test Automation Engineer
QA Engineer / Test Automation EngineerContributions:11 commits in 1 year 4 months
Contributions summary:Yuichi primarily contributes to the testing framework of the Fluentd project. Their commits focus on adding tests for mixin functionalities, including `SetTagKeyMixin`, `SetTimeKeyMixin`, and `HandleTagNameMixin`. Furthermore, they modify existing tests and incorporate `sed` unbuffered support, indicating involvement in maintaining and enhancing the test suite's coverage and compatibility.
fluentdloggingdata-collectorrubycncf
hotchpotch/JQaRA
Mar 2024 - Sep 2025
JQaRA: Japanese Question Answering with Retrieval Augmentation - 検索拡張(RAG)評価のための日本語Q&Aデータセット
Contributions:26 PRs, 25 pushes, 24 branches in 1 year 6 months
question-answeringinformation-retrievalnlp
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