Dr Bezerianos kicked of his presentation by introducing mental workload estimation as a significant neuroscience problem. Dr Bezerianos presented his group’s network based method for feature selection and classification of mental workload from two independent tasks, which had a satisfactory accuracy of 82% on cross-task workload classification, and was stable using 26 to 42 features.