Manual artifact detection in multi-channel EEG signals required 14 hours per patient dataset during epilepsy diagnostics clinical trials.
Trained a custom 1D-CNN transformer architecture in PyTorch with spectral wave decomposition, paired with a Next.js visualization interface for researchers.
“I was terrified of my FYP defense until my mock sessions with Hopfield Labs. They helped me grasp every single convolution layer and backpropagation step in my thesis. I walked away with an A+ and Highest Honors.”
We evaluate new project briefs and engineering requirements within 12 hours.