I architect and implement distributed systems, compilers, and AI infrastructure. My focus is on correctness, performance, and maintainable design at scale.
Three core domains where I build production systems and solve complex technical challenges.
Distributed key-value stores, consensus algorithms, and high-performance networking. I build systems that handle failure gracefully and scale horizontally.
LLVM-based compiler development, static analysis, and code generation. Deep understanding of how high-level code becomes efficient machine instructions.
Production ML systems, computer vision pipelines, and AI-powered applications. Focus on efficient model serving and real-world deployment challenges.
Selected projects demonstrating systems thinking, technical depth, and production-ready implementation.
Continuous problem-solving practice and algorithmic thinking through competitive programming platforms.
Identify underlying algorithmic patterns and data structure requirements before coding.
Analyze time and space complexity to optimize solutions for scalability.
Comprehensive testing with boundary conditions and corner cases.
My systematic approach to building reliable, maintainable systems that scale from prototype to production.
Requirements analysis, constraint identification, and performance target definition
System design with modularity, testability, and operational simplicity
Iterative development with continuous validation and comprehensive monitoring
I approach engineering with a curiosity-driven, first-principles mindset, focusing on why systems are designed the way they are and how they behave under failure. I believe strong engineering comes from understanding constraints and trade-offs, not just implementations.
I am interested in AI and emerging technologies, but I ground my work in fundamentals. I aim to build systems that are explainable, robust, and designed with intent rather than trends.
Every project teaches something new about performance, reliability, or maintainability. I approach problems with understanding the constraints, designing for the expected load, and building observability from day one.
Interested in discussing systems architecture, compiler design, or engineering challenges? I'm always open to interesting conversations.