A student exploring how computational systems are built — from programming languages and virtual machines to hardware and formal models.
I'm interested in understanding systems by building small versions of them.
- Building small interpreters and virtual machines from scratch.
- Exploring the path from source code → AST → IR → bytecode → runtime.
- Learning how different computational models can represent each other.
- Exploring RISC-V processors and hardware design with Chisel.
- Studying pipelines, hazards, memory systems and verification methods.
- Using simulation and formal modeling to understand hardware behavior.
- Learning TLA+ for describing concurrent systems and state transitions.
- Experimenting with executable models to reason about complex designs.
- Languages: Python, Scala, C/C++, Rust (learning)
- Hardware: Chisel, Verilog/SystemVerilog, Bluespec SystemVerilog
- Modeling: TLA+
- Systems: Linux, RISC-V ecosystem
I learn by building.
Small experiments, incomplete prototypes, and imperfect models are often the fastest way for me to understand a system.
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*"A system is understood when you can build a smaller one."* ✍️