Graduate Student Research Achievements Site | Ritsumeikan University

（Last updated : 2026-07-28 09:29:08）

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HAMID Baizid Al

Department / Course Ritsumeikan University Graduate School Graduate School of Information Science and Engineering Major in Information Science and Engineering

Job

Academic background
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 Graduated

Academic conference attendance and presentation
2026/07/08	Automating Legal Statute Matching in Online Petition Systems (International Conference on eDemocracy & eGovernment (ICEDEG))

Website
About Me

Internship History
GeoRhizome Ltd. AI Engineer

Skills
IELTS (Academic) Score: 8.0
TOEIC Listening & Reading Score: 960

Self and Research introduction
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.

External Scholarship and Research Grants receiving status
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)