01 About
An engineer who reads code closely | And a researcher drawn to machine learning and data.
I studied Computer Science & Engineering at NWU, where learned and practiced the fundamentals of Computer Science and Software Engineer. My research work was to read Bengali handwritten characters from image using CNN.
Can a system learn from messy, real-world data well enough to be trusted in production? That question is what pulls me from engineering toward research.
Since then I’ve worked across the stack in production teams — a distributed logging pipeline handling a million entries a day, a secure file-serving platform on AWS, high-throughput preprocessing services, and Android apps with real users. Most of that work is the slow, careful business of understanding code that already exists.
My research interest is machine learning and data science applied to software engineering: building and evaluating models that learn from real-world data and hold up in production. It sits exactly where my two threads meet - the rigour of academic evaluation on one side, the messy reality of production codebases on the other.
Distributed systemsSoftware engineeringApplied MLCloud & DevOps