ML / systems engineer working across Python, Rust, PyTorch, and TypeScript.
I like building things where modeling, algorithms, and systems implementation meet: compression, search, probabilistic interfaces, performance-conscious data structures, and interactive tools.
Portfolio: https://khoda81.github.io/
- Chronickle — interactive market-intelligence timeline that aligns price movement and real-world news on one scrubbable canvas. Live demo
- natwalk — navigate autoregressive model distributions in information space, using exact arithmetic-code actions and Dijkstra search in surprisal.
- mercy — experimental Rust interface for composable arithmetic coding built around a fixed 64-byte boundary representation.
- logvec — cache-friendly Bentley–Saxe logarithmic data structure in Rust, with benchmark comparisons against
BTreeSetand sorted vectors. - rust-2048-solver — performance-focused 2048 search in Rust with compact board operations, heuristic evaluation, caching, and benchmarks.
- dethcod — research project exploring learned lossless compression with transformer models.
- language models and probabilistic interfaces
- neural and classical data compression
- reinforcement learning, search, and online adaptation
- Rust / Python interoperability
- performance-conscious data structures and developer tools
- interactive, data-intensive applications
Languages: Python, Rust, TypeScript, JavaScript
ML/data: PyTorch, Transformers, reinforcement learning, NLP
Systems/web: Linux, WebAssembly, SolidJS, Vite, Bun
Development: Git, Jujutsu, testing, benchmarking, package publishing
I'm open to part-time remote contract and research-oriented engineering work involving ML, Python, Rust, or systems-heavy AI tooling.


