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Andrea Stocco & Catherine Sibert

University of Washington

Andrea Stocco

Andrea Stocco is a computational cognitive neuroscientist at the University of Washington, Seattle. Andrea’s research focuses on characterizing the architecture of the human brain from a computational perspective, investigating the algorithms are used by brain circuits and how they could be identified from behavioral and neural data. His research aims to develop high-fidelity models of brain function that can be used to create new technologies that support or augment human cognition in patients and healthy subjects. In his work, Andrea has used multiple methods, including EEG, fMRI, and neurostimulation techniques. In 2013, he developed the first non-invasive direct brain-to-brain interface. 

Catherine Sibert

Catherine first became interested in Cognitive Science because of a childhood interest in robots, but quickly decided that the human mind was fascinating enough on its own. She collected a complete set of Cognitive Science degrees from Rensselaer Polytechnic Institute, studying human performance, skill acquisition, and expertise in complex, dynamic tasks, using the video game Tetris as a test case. Specifically, her work  explored the environmental factors that gave rise to specific task strategies by manipulating the task space of high performing machine learning models and comparing them to complex human data. She is now working as a PostDoc at the University of Washington, studying the human mind at a much lower level, trying to understand low level brain data through the framework of cognitive architectures.

“Exploring Cognitive Architectures in the Era of Large Brain Data”