Data science, from first principles to production.

I'm a cloud and AI architect with 17 years of experience in IT, working with top-tier companies along the way. Over that time I've moved from building and running systems to architecting the platforms and models that make them smarter: cloud, machine learning, deep learning, and, more recently, generative AI.

My academic path mirrors that focus: a B.Tech in Information Technology, an Executive Post Graduate Diploma in Data Science, and a Master's in Data Science with a thesis on detecting medicinal plant leaves using deep neural networks and transfer learning. During my postgraduate studies I led projects in machine learning and generative AI, from boosting sales efficiency for an EdTech firm to building gesture recognition for smart TVs. I pursued that journey while balancing my role as a dedicated mother.

I'm also a Microsoft Certified Solutions Expert in Cloud Platform and Infrastructure, which keeps me grounded in the realities of shipping this work on Azure. What interests me most is the practical side of AI: the data quality, honest evaluation, and engineering that decide whether a model is genuinely useful or just a convincing demo. When I work something out, I try to write it down here.