I am a computer scientist, schizophrenia researcher, and an expert in electroencephalographic (EEG) data collection. I record brain activity in children and young adults at risk for developing psychosis, and in individuals diagnosed with schizophrenia. I hold a masters degree in software engineering which I use to design experimental tasks for use on the web. Additionally, I am responsible for mentoring our graduate students and postdocs in applying computer science methods to their data collection and analysis. I am also interested in the application of computational neural networks to EEG data.
My current research measures audio-visual integration, a biomarker that may be useful in understanding how social information is processed in the brain. I am developing a psychophsiological prediction model, based on the McGurk-MacDonald Illusion, to preemtively indentify those at risk for developing psychotic disorders.
My aim to develop a treatment target based on this paradigm, with the goal of modeling interventions to reverse the developmental trajectory of psychotic disorders.