cv.zekkx.icu

Shibo Yan（厳 世博）

厳 世博 · ゲン セイハク

~ $ cat role.txt

open to opportunities session 00:00:00 scroll ↓
01 About 01 / 05

About Me

Based in Tokyo, with a background in automation engineering and systems work. Hands-on with server operations, AI tooling, and quantitative analysis — now researching AI's measurable impact in Japan's IT sector.

Currently working on empirical research targeting listed IT companies in Japan: panel data methods, event studies, Python-based workflows. From infrastructure setup to analysis and interpretation.

Technical background, research mindset — looking to bring both into an IT role.
02 Skills 02 / 05

Skills

Skill matrix
Skill Level Evidence
Data & Analysis
Statistical modelingProficientMCM/ICM 2020 · Master's thesis
Panel regressionProficientMaster's thesis (FE / RE / CRE)
Event studyProficientMaster's thesis
SPSS · MATLABWorkingMCM/ICM 2020
PythonLearningResearch data processing
Accounting & Finance
BookkeepingWorkingBookkeeping Grade 2 (簿記2級)
Financial statement analysis · Management accounting · Corporate financeWorkingGraduate coursework
Languages
ChineseNative—
JapaneseBusinessJLPT N1
EnglishWorkingCET-4 · 525
03 Projects 03 / 05

Projects

  1. [01] IEEE Conference Paper · 2026 Co-first Author

    A Regulatory Placebo: The Failure of Mandatory GenAI Labeling

    Jingyi Chen†, Chaofan Bu†, Xuesong Li*, Shibo Yan†

    Compares mandatory labeling of AI-generated content across five jurisdictions and argues it works as a regulatory placebo — hard to enforce, technically self-defeating, and weakly justified. Proposes content- and risk-based governance instead.

    • GenAI Governance
    • Watermarking
    • Comparative Law
  2. [02] Master's Thesis · Ongoing

    AI Adoption & Financial Performance

    Investigating whether AI-related disclosure in corporate annual reports reflects genuine operational transformation or strategic narrative — and how this distinction relates to financial performance in Japan's listed IT sector.

    • Empirical Research
    • Panel Data
    • Corporate Finance
  3. [03] MCM/ICM 2020 · Problem E

    Plastic Waste Modeling

    Built a multivariate nonlinear regression model combined with a grey prediction system to estimate global disposable plastic waste thresholds. Applied TOPSIS-based environmental carrying capacity evaluation across four major world regions, analyzing production and recycling data from 2005 to 2017.

    • Mathematical Modeling
    • Statistical Analysis
    • Environmental Systems
04 Education 04 / 05

Education

  1. 2025 — 2027

    Meiji UniversityM.Acc.

    School of Professional Accountancy · Accounting

    Tokyo · Japan

    Research: AI adoption and corporate financial performance in Japanese markets

    progress --%
  2. 2018 — 2022

    Southwest UniversityB.Eng. + B.A.

    Control Engineering + Japanese Studies

    Chongqing · China

05 Contact 05 / 05

Get in Touch

Email
shibo_yan@outlook.jp
ORCID
0009-0003-5447-7744
Institution
Meiji University · Graduate School of Professional Accountancy
Location
Surugadai Campus · Chiyoda-ku, Tokyo
Status
M.S. 2nd Year · Expected March 2027