Ms. Jimy John Mathew

Ms. Jimy is a Lecturer in Computer Science at the University of Stirling, Ras Al Khaimah Campus, UAE. Jimy holds a Bachelor’s in Computer Application from Birla Institute of Technology, Ras Al Khaimah, Masters in Big Data from University of Stirling, Ras Al Khaimah Campus, Postgraduate Certificate in Learning and Teaching in Higher Education (PGCLTHE) from the University of Stirling, UK and is a Fellow (FHEA) in the Higher Education Academy, UK. Her academic interests lie in Artificial Intelligence, Machine Learning, Data Science, and Software Engineering, with a strong focus on developing practical, industry-oriented learning experiences.

Jimy combines research-led teaching with applied computing to equip students with the technical and analytical skills needed to address real-world challenges. Alongside her teaching responsibilities, she supervises undergraduate research projects in artificial intelligence (AI), data science, computer science, and software engineering, while actively contributing to research in intelligent systems and sustainable computing. She has earned professional qualifications in AWS Machine Learning Certification Training, IBM Python for Data Science, and IBM Data Science certifications.

Prior to joining the University of Stirling, Jimy served as an Academic Tutor, delivering courses in software development, SQL databases, web technologies, Object Oriented analysis and design, programming, statistics, and professional computing. At the University of Stirling, she teaches undergraduate modules in artificial intelligence, machine learning, data science, software engineering, programming language paradigms, user interface design, and programming using Java, Python, and C++. She also mentors undergraduate research projects, supporting students in applying technical knowledge to address emerging industry challenges.

Jimy's research focuses on the application of machine learning and deep learning to sustainability, intelligent vision systems, predictive analytics, educational analytics and innovations. Her recent work includes CO₂ emission prediction and optimization, intelligent waste classification, aircraft fuel optimisation, and graduate attributes in higher education. She has published in international conference proceedings, journals and continues to contribute to peer-reviewed journals, conference papers, and book chapters in AI and data science. Through her research and teaching, she is committed to advancing innovative, data-driven solutions while fostering research-led education.