NeuroAI → Brain-Computer Interfaces
I work in NeuroAI 🧠. I take raw neural signal and build the machine learning and deep learning models that turn it into insight 💡 — and take them all the way to deployment as data products 📦, not notebooks. I'm a builder at heart 🛠️ — I own problems end to end, from the first messy dataset to a working system.
I'm building toward brain-computer interfaces 🤖. The decoding work I do now is the groundwork: the better a model reads meaning from neural signals, the closer those interfaces come to being real. That's where I'm headed. 🚀
Recent Posts
-
From 86% to 71%: learning to trust a brain decoder's accuracy
I trained a tiny CNN to read MEG brain signals on Colab. The interesting part wasn't the model — it was how stratified splits, checkpoint hygiene, and cross-validation deflated a flattering 86% into an honest 71% ± 5%, and revealed exactly where the model wins.
-
How I use Google Colab
Notes and recipes from my day-to-day Google Colab workflow — setup, data handling, and package installs.