{"675956":{"#nid":"675956","#data":{"type":"event","title":"PhD Defense | Building foundation models for neuroscience","body":[{"value":"\u003Cp\u003EMehdi Azabou - Machine Learning PhD Student - School of Electrical and Computer Engineering\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDate: \u003C\/strong\u003ETuesday, August 20, 2024\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETime: \u003C\/strong\u003E2:30 PM \u2013 4:30 PM\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ELocation: \u003C\/strong\u003ECoda C1115 Druid Hills\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EMeeting Link: \u003C\/strong\u003E\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/97816662750\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/97816662750\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E1 Dr. Eva L. Dyer, Advisor, School of Biomedical Engineering, Georgia Tech\u003C\/p\u003E\u003Cp\u003E2\u0026nbsp;Dr. Chethan Pandarinath,\u0026nbsp;School of Biomedical Engineering, Georgia Tech\u003C\/p\u003E\u003Cp\u003E3 Dr. Anqi Wu, \u0026nbsp;School of Computational Science and Engineering, Georgia Tech\u003C\/p\u003E\u003Cp\u003E4 Dr.\u0026nbsp;Hannah Choi, \u0026nbsp;School of Mathematics, Georgia Tech\u003C\/p\u003E\u003Cp\u003E5 Dr. Blake Richards, School of Computer Science and Montreal Neurological Institute, McGill University\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EThe brain\u2019s complexity enables its remarkable functions, but this very complexity makes it hard to understand. Current methodologies for recording brain activity often provide narrow views of the brain\u0027s function, limited by the constraints of current recording technology and the structured nature of the standard neuroscience experiment. This fragmentation of datasets has hampered the development of robust and comprehensive computational models of brain function that generalize across diverse conditions, tasks, and individuals. Our work is motivated by the need for a large-scale foundation model in neuroscience--one that can go beyond the limitations of single-dataset approaches and offer a fuller, more comprehensive picture of brain function. In this thesis, we propose novel methodologies and frameworks aimed at addressing the challenges of building such a model. We discuss three main contributions. The first contribution is towards building scalable and unified approaches for training on diverse neural datasets. The second contribution aims to develop self-supervised methods for understanding dynamics of behavior at multiple timescales. The third contribution is to develop methods for building invariances in neural data to further our understanding of the brain.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EBuilding foundation models for neuroscience\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Mehdi Azabou - Machine Learning PhD Student - School of Electrical and Computer Engineering"}],"uid":"36518","created_gmt":"2024-08-13 17:14:45","changed_gmt":"2024-08-13 17:14:45","author":"shatcher8","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2024-08-20T14:30:00-04:00","event_time_end":"2024-08-20T16:30:00-04:00","event_time_end_last":"2024-08-20T16:30:00-04:00","gmt_time_start":"2024-08-20 18:30:00","gmt_time_end":"2024-08-20 20:30:00","gmt_time_end_last":"2024-08-20 20:30:00","rrule":null,"timezone":"America\/New_York"},"location":"Coda C1115 Druid Hills","extras":[],"groups":[{"id":"576481","name":"ML@GT"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"174045","name":"Graduate students"},{"id":"177814","name":"Postdoc"},{"id":"78761","name":"Faculty\/Staff"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}