Engineering reliable software through first principles

My path into computer science began with customizing Linux kernel modules and investigating memory management bottlenecks. That early curiosity evolved into rigorous academic research and production-minded software engineering.

I prioritize predictable latency, robust type systems, and maintainable codebases over short-term hacks. Every architecture decision is measured against real-world constraints and operational telemetry.

Core technical domains

Specialized areas grounded in academic theory and practical implementation.

Systems Programming

Web Infrastructure

Data Modeling

Low-level memory management, concurrent execution models, and performance profiling using Rust and C.

Scalable service architectures, typed API contracts with TypeScript and Go, and resilient containerized deployments.

Relational schema design, query optimization, and consistency guarantees in distributed PostgreSQL environments.

Minimizing complexity in modern toolchains

Software reliability scales inversely with hidden dependencies. By aggressively auditing third-party modules and writing comprehensive integration tests, we eliminate silent failure modes before code reaches production environments.

Documentation is treated as a primary feature, not an afterthought. Clear architectural decision records and readable codebases ensure teams can onboard quickly and iterate with confidence.

Available for Q3/Q4 2025 engineering internships, fellowships, and collaborative research initiatives.