大学院生研究業績サイト

（最終更新日 : 2026-07-28 09:29:08）

Visruth.jpg not found

ハミド　バイジド　アル HAMID Baizid Al
HAMID Baizid Al

所属立命館大学大学院情報理工学研究科情報理工学専攻

職種正規生

学歴
2026/04/01～	Information Science and Engineering Course Graduate School, Division of Information Science Ritsumeikan University
2022/04/01～2026/03/31	Information Systems Science and Engineering College of Information Science and Engineering Ritsumeikan University 卒業

学会発表
2026/07/08	Automating Legal Statute Matching in Online Petition Systems (International Conference on eDemocracy & eGovernment (ICEDEG))

ホームページ
自己紹介

インターンシップ歴
株式会社ジオリゾーム AIエンジニア

技術・スキル
IELTS (Academic) Score: 8.0
TOEIC Listening & Reading Score: 960

自己PR・研究紹介
My name is Baizid Al Hamid and I am originally from Bangladesh. I am currently a Master's student in Information Systems Science and Engineering at Ritsumeikan University (OIC Campus Osaka) and I am affiliated with the Digital Governance Systems Laboratory under Prof. Serdült Uwe Imre. I hold a strong interest in applying machine learning and natural language processing to real-world governance and public administration challenges. This interest has shaped both my academic research and my practical software development work including a paid internship engagement at Georhizome Co. Ltd. My research focuses on Natural Language Processing and Large Language Models applied to e-government and legislative systems and in particular the challenge of connecting informal citizen input such as online petitions to formal legal frameworks. My Master's thesis proposes an embedding based hybrid retrieval system that combines dense semantic search sparse keyword matching (SPLADE) and HyDE based query expansion with cross encoder reranking in order to automatically match citizen petitions with relevant UK legislation from a corpus of over 110000 laws. This work was presented at ISCSP in Lisbon, Portugal and demonstrated that automated retrieval can substantially reduce the manual burden on civil servants while maintaining high accuracy and offering a scalable pathway toward more responsive digital government systems. I am now expanding this presented and published work to incorporate Explainable AI (XAI) justification so that retrieved legal matches can be accompanied by transparent and interpretable explanations suitable for use by civil servants and policymakers. My broader research interests include pre-trained language models for legal domains such as LexLM few-shot learning, and probing tasks for legal language understanding such as LegalLAMA, all aimed at making legislative and administrative processes more transparent and accessible.

学外奨学金・研究助成金獲得状況
2022 2023	JASSO Scholarship (日本学生支援機構奨学金)
2024 2025	JASSO Scholarship (日本学生支援機構奨学金)
2026 2027	NITORI International Scholarship (公益財団法人似鳥国際奨学財団)