I’m an AI & Data Science undergraduate driven by systems thinking and real-world impact.
I don’t just experiment with models — I build complete, production-ready systems around them.

My work sits at the intersection of AI engineering, backend architecture, and cloud infrastructure.
I enjoy designing scalable pipelines, integrating ML into full-stack applications, and solving complex engineering problems under constraints.

Hackathons sharpened my execution speed. Research sharpened my analytical depth.
Now I focus on building systems that are reliable, scalable, and architecturally sound.

I’m especially interested in:
- AI systems that operate in production environments
- Workflow and automation engines
- Secure, cloud-native backend architectures
- Performance-first engineering

I believe clean architecture beats feature bloat.
If it scales cleanly, it survives.