Neural Engineering Projects

I learned how to analyze neurological data and establish neural correlates of behavior.

• TensorFlow Seizure Classification (Python)

• Neural Engineering Portfolio

• Utilized TensorFlow, Keras, and Eager Execution to train recurrent neural network that classify seizures in EEG dataset

• Achieved 88.89% training accuracy and 87.56% testing accuracy with 50 neuron, 3 hidden layer network architecture

• Data Driven Problem Solving, this course taught me how to design electrodes to tap into the brain, what kinds of things happen in relation to tissue impedance, what it takes to get denoised, high spatio-tempo-resolution data from the brain, and how to analyze it using various signal processing methods ranging from continuous decoders such as kalman filtering to deep learning techniques.