Lamis GHOUALMI

I am a highly motivated scientist with a strong data analysis, data science, and academic research background. I hold a Ph.D. in Computer Science, where my research focused on solving biometric challenges using bio-inspired artificial intelligence. Specifically, I modeled biometric tasks, such as image enhancement, data selection, reduction, and fusion, as optimization problems. My interests lie in interdisciplinary work, where I apply my computer and data science expertise to support analysis, prediction, and the development of innovative solutions for informed decision-making. In my current role, I design and implement ETL pipelines, manage and optimize enterprise databases, and develop Power BI dashboards to drive data-informed strategies. I work closely with IT, operations, and stakeholders to define requirements and resolve integration challenges. I also leverage data fabric technologies to enable unified and intelligent data access across diverse systems. Additionally, I actively explore the use of AI in higher education, leading projects such as AI-powered data cleaning, major recommendation systems, and other initiatives aimed at improving student success and institutional effectiveness. I regularly present this work at academic and IT conferences, bridging the gap between innovation and practical application. In academia, I have mentored students on research projects, supervised theses, and taught university-level computer science and data science courses. These experiences have strengthened my commitment to high-quality, impactful education and research, while keeping me closely engaged with emerging technologies and methodologies.

Keywords: Data analytics, Data science, Machine learning, Artificial intelligence (AI), pattern recognition, optimization.