Introduction
I'm an independent learner moving toward neuroengineering. I treat learning, research, and engineering as one continuous practice rather than separate phases.
This site is both a public notebook and a quiet commitment device — what I publish here is what I am actually working on.
Research Direction
Brain–computer interfaces, with a focus on robust decoders, calibration-free models, and signals that survive real-world noise. I am especially drawn to systems that can eventually restore function for patients.
Learning Path
Deepening BCI foundations
2025 —- Signal processing, computational neuroscience, decoder architectures
- Reproducing EEG decoding baselines end-to-end
- Weekly reading log across neuroscience and ML
Engineering practice
2024- Local-first notes system, data pipelines, small ML systems
- Rust and C for the parts where precision matters
- Linux, shell, and reproducible workflows
Starting the long path
2023- First serious neuroscience reading list
- Parallel deepening of math and programming
- First Kaggle notebooks — habit over hype
Projects
Small projects I can finish, ship, and learn from: an EEG decoding pipeline, a literature notes app, a minimal spike sorter, and an ongoing daily learning log.
Technical Skills
Programming Languages
Tools
AI / ML
BCI / Neuroscience
Engineering / Workflow
Long-term Goal
To do honest work at the intersection of neuroscience and engineering — work that helps real people, and that I can defend at every layer of the stack.