📍 M.S. Software Engineering @ Carnegie Mellon University | 💻 Former Software Engineer @ Microsoft
Despite being an avid reader, I’ve always chosen to ground my understanding through hands-on code rather than poring over heavy theory.
Over the years, I’ve explored and worked across multiple domains:
- applied AI/ML (scikit-learn etc., ML frameworks/Pytorch/Tensorflow)
- frontend stack (React/TS/CSS libraries),
- backend services (C++/Python/JS) and
- android dev (Java/Kotlin/Flutter),
Today, I'm a Software Engineering grad student at Carnegie Mellon University, studying at the intersection of AI and high-performance systems.
Previously, I was a Software Engineer at Microsoft with experience building AI-forward applications and having owned full-stack feature lifecycles (React/TypeScript frontend, .NET/C# backend, Azure)
Having worked on the application layer of AI-integrated software systems, I'm now learning what's under the hood and how to optimise performance across both layers.
- Systems for AI & Distributed inference
- ML compilers and kernel-level optimisation
- Model serving infrastructure
- Diffusion-based LLMs
(stay tuned for progress!)
- Shipped AI-powered features for Enterprise applications
- Designed & worked on an Agentic AI Platform
- Backend orchestration for LLM workflows
- End-to-end ML pipelines from model logic to deployment
(but not limited to)
