معرفی
Edmund Lalor is an Associate Professor in the Departments of Biomedical Engineering and Neuroscience at the University of Rochester. He holds a B.E. in Electronic Engineering (University College Dublin, 1998), M.Sc. in Electrical Engineering (University of Southern California, 1999), and a PhD in Biomedical Engineering (University College Dublin, 2006). His research focuses on quantitative modeling of sensory electrophysiology in humans, particularly examining neural processing of natural stimuli like speech and video. Key areas include attentional mechanisms, multisensory integration, and clinical applications in schizophrenia and developmental disorders.
Educations: B.E. (Electronics), UCD (1998); M.Sc. (Electrical Engineering), USC (1999); PhD (Biomedical Engineering), UCD (2006).
Research interests emphasize computational neuroscience, cortical tracking of natural speech, and the neural basis of sensory processing deficits in clinical populations. His work combines EEG analysis with deep learning techniques to decode attentional selection and improve brain-computer interfaces. Collaborations include studies on auditory processing in schizophrenia and neurophysiological correlates of language comprehension in aging populations.
Scientific contributions include developing the mTRFpy Python package for temporal response function analysis, and pioneering EEG-based methods to decode attended speech in multispeaker environments. Current efforts explore how context and attention shape neural encoding of linguistic meaning through dynamic modeling approaches.
