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Thesis supervision | Stepan Bolotnikov: Fuzzy Classification Algorithms in Brain-Computer Interfaces

In this thesis, the usage of fuzzy classification algorithms in brain-computer in- terfaces (BCI) based on electroencephalography (EEG) is researched. We review the existing literature on BCI, the traditional crisp algorithms often used in BCI for classification, fuzzy classification algorithms and their application in BCI. A simple BCI system is implemented that allows the user to move a cursor on the computer screen. Tests conducted with this application did not show that fuzzy classification algorithms have advantage over crisp classification algorithms in this kind of BCI systems.

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I have worked on various projects in machine learning and computer science, neuroscience and brain-computer interfaces, reinforcement learning and robotics. Currently I am focusing on two things: leading machine learning team at OffWorld Inc. to train robots for space exploration, and continuing the research done as part of my PhD on neuroscience and artificial intelligence.

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