I hold a strong academic foundation in mathematics and statistics, complemented by active research interests in artificial intelligence and machine learning. My formal education includes a M.Sc. in Big Data Analytics , where I developed a deep understanding of both theoretical and applied aspects of mathematical sciences.

Over the past few years, I have been engaged in teaching mathematics and statistics at the undergraduate and postgraduate levels. My teaching experience covers core subjects such as linear algebra, calculus, probability theory, statistical inference, and regression analysis, as well as specialized topics in data science, machine learning, and deep learning.

As an educator, I emphasize conceptual clarity, mathematical rigor, and real-world applications. I often integrate Python and R in my teaching to help students bridge theory and practice. I also design assignments and mini-projects that encourage independent thinking and research-oriented learning.

This combination of research and teaching allows me to bring a contemporary and interdisciplinary perspective into the classroom, ensuring that students are equipped with both foundational knowledge and relevant computational skills.