Update README.md

README.md

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 TensorFlow and Keras implementation of Zhang et al(2018), "EEG-based Intention Recognition from Spatio-Temporal Representations via Cascade and Parallel Convolutional Recurrent Neural Networks" for EEG motar imagery classification on PhysioNet data (https://www.physionet.org/pn4/eegmmidb/). Stacked CNN and RNN were applied on time-distributed sliding windows of raw EEG data.
 
+### Columbia Data Science Institute (DSI) Conference
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 Acamdemic Reference
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 eeg_eval.py                       | Evaluation of the model based on the history file. - calls the confusion matrix, loss, and accuracy.
 eeg_prepare.py                    | Preprocess the imported EEG data. 
 gpu_training.sh                   | Send the eeg_main.py script to the computational nodes. Enter 'sbatch gpu_trainin.sh' on Habanero HPC.
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