About me

I am an Assistant Professor and Data Scientist working at the intersection of computer vision, machine learning, and biomedical imaging.

My research focuses on developing AI-driven methods for image analysis, with applications in healthcare, scientific imaging, and real-world systems. During my PhD, I worked on detecting complex patterns using colour and texture features, which laid the foundation for my current work in data science and artificial intelligence.

I have been involved in innovation-driven projects across domains such as medicine, mining, and retail, where I have developed and deployed machine learning and computer vision solutions. My experience includes full-cycle data science workflows, from data acquisition and preprocessing to model development, deployment, and stakeholder-oriented analysis.

I work primarily with Python and R, and have hands-on experience in areas such as computer vision, natural language processing, and generative AI, with a strong focus on model evaluation, ethical AI, and data privacy.

Alongside my research, I am deeply committed to teaching and mentorship. I have taught courses ranging from foundational mathematics and physics to advanced topics in electrical engineering, and I actively supervise student research in AI and computer vision.