About

Portrait of Shinya Uryu, outdoors under a blue sky.

Portrait of Shinya Uryu

Shinya Uryu (瓜生 真也) is an Assistant Professor at the Center for Design-Oriented AI Education and Research, Tokushima University, with a joint appointment in the Faculty of Science and Technology.

Trained in forest ecology, he worked as a data engineer in industry and at the National Institute for Environmental Studies before joining Tokushima University in 2021. His research applies data analysis, machine learning, and language processing to human–nature interactions — heat illness risk under climate change, wildlife trade in online markets, and the multilingual structure of biodiversity knowledge. He builds most of his work in R and Python, and maintains a number of open-source R packages.

GitHub · ORCID · researchmap · Google Scholar · Speaker Deck · X (@u_ribo)

Positions

  • 2021–present — Assistant Professor, Center for Design-Oriented AI Education and Research, Tokushima University (since 2024, also Faculty of Science and Technology)
  • 2017–2021 — Research technical specialist, National Institute for Environmental Studies (NIES): data engineering and R package development for biodiversity conservation and sustainable use of environmental resources
  • 2016–2017 — Data analyst, Nightley Inc.: location data analytics and tool development

Education

  • 2014 — M.S. in Environmental Studies, Graduate School of Environment and Information Sciences, Yokohama National University (forest ecology)
  • 2012 — B.S., Department of Biosphere-Geosphere System Science, Okayama University of Science

Books

  • Rユーザのためのtidymodels〈実践〉入門 (co-author; Gijutsu-Hyoron, 2023) — a practical introduction to modern statistical and machine learning modeling with tidymodels
  • データ分析のためのデータ可視化入門 (translator; Kodansha Scientific, 2021) — Japanese translation of Kieran Healy, Data Visualization: A Practical Introduction
  • Rによるスクレイピング入門 (co-author; C&R Institute, 2017) — web scraping with R

Talks & Outreach

Invited talks, seminars, and courses for industry, local communities, and the public. Conference presentations are listed on researchmap.

  • 2026 — 生成AIによるデータ分析の支援と実践：適切な利用と再現可能性研究 (“Supporting data analysis with generative AI: practice, appropriate use, and reproducible research”), seminar, Japanese Society of Computational Statistics (October 31, online)
  • 2026 — 明日からでも使えるAI・DS実践講座 (“Practical AI and data science you can use from tomorrow”), course for working adults, Tokushima Recurrent Education Program (October–November)
  • 2026 — AIの基礎知識について (“Basics of AI”), invited talk at a briefing for accommodation operators in Tokushima Prefecture (September)
  • 2025, 2026 — 生成AIツール活用セミナー (“Seminar on generative AI tools”) and a follow-up seminar for local business owners, Komatsushima Chamber of Commerce and Industry
  • 2022–2026 — Annual public extension course for working adults, Tokushima University:
    • 2026: はじめての生成AI活用：仕事の文書・資料づくり実践講座 (“Getting started with generative AI: writing documents and materials at work”)
    • 2025: はじめてのAI活用術：仕事に活かす基礎と実践 (“Getting started with AI: basics and practice for work”)
    • 2024: 仕事で役立つ人工知能（AI）エンジニアリング (“AI engineering for work”)
    • 2023: 仕事ではじめるデータサイエンス・AI（入門編） (“Data science and AI at work: an introduction”)
    • 2022: ビジネスに役立つデータ分析（入門編） (“Data analysis for business: an introduction”)
  • 2025 — 「Positron」によるAI・データサイエンス〜R、Pythonユーザーのための次世代IDE (“AI and data science with Positron, a next-generation IDE for R and Python users”), seminar, Japanese Society of Computational Statistics
  • 2025 — 技術士×AI：社会課題を解決するイノベーションの原動力 (“Professional engineers and AI: driving innovation to solve social challenges”), invited talk, The Institution of Professional Engineers, Japan (Tokushima)
  • 2024 — 生成AIの基礎的事項と社会に与える影響 (“Generative AI: fundamentals and social impact”), invited lecture for court staff
  • 2024 — 計算機統計学研究における再現可能性の課題と解決策 (“Reproducibility in computational statistics research: problems and solutions”), invited seminar, JSCS Forum 2024
  • 2024 — Rユーザのための機械学習チュートリアル (“A machine learning tutorial for R users”), invited tutorial, Japan Statistical Society Spring Meeting
  • 2023 — 次の一歩を踏み出すためのtidyverse入門 (“An introduction to the tidyverse for taking the next step”), online workshop, The Institute of Statistical Mathematics
  • 2022 — 徳島県内在住者における移動時の行動様式と健康状態の分析 (“Mobility patterns and health status of residents of Tokushima Prefecture”), Shikoku Open Innovation Workshop
  • 2022 — Rによるデータ可視化と地図表現 (“Data visualization and mapping with R”), online workshop, The Institute of Statistical Mathematics
  • 2021 — Rによるデータ解析のためのデータ可視化 (“Data visualization for data analysis with R”), invited tutorial (co-taught), Japanese Joint Statistical Meeting
  • 2019 — データ分析における特徴量エンジニアリング〜多種多様なデータを扱う際の原理と実践〜 (“Feature engineering for data analysis: principles and practice”), seminar for industry practitioners, Johokiko (Tokyo)
  • 2018 — Rを用いた地理空間データの操作と可視化 (“Geospatial data manipulation and visualization with R”), invited talk, FOSS4G 2018 Tokyo
  • 2017 — モダンな方法で学ぶ、Rによる地理空間情報データの処理 (“Processing geospatial data with R the modern way”), invited talk, FOSS4G Hokkaido 2017