Md Nazmul Hasan

Md Nazmul Hasan is a graduate student in the School of Environment, Enterprise and Development at the University of Waterloo. His research applies artificial intelligence (AI) and multimodal learning to strengthen governance systems in small-scale fisheries (SSF). By integrating machine learning and natural language processing (NLP), he works to unify fragmented governance data, including policy texts, community narratives, government signals, and institutional archives, into participatory decision-support tools that enhance community engagement and enable transitions from vulnerability to viability. Before his graduate studies, he worked as a Data Analytics and Statistical Consultant, developing statistical models, data pipelines, and visualization dashboards to support evidence-based decision-making. Earlier, as a Research Assistant in the Department of Plant Sciences at the University of Saskatchewan, he conducted research on plant genome sequencing. He also worked as a Data Analyst with the Faculty of Health at the University of Waterloo for a brief period. He holds an M.Sc. in Mathematics from the University of Saskatchewan and an Advanced Diploma in Software Engineering Technology with distinction from Conestoga College. His interdisciplinary background combines environmental governance, machine learning, and data-driven analysis to develop adaptive and inclusive governance for social-ecological systems.