{"689414":{"#nid":"689414","#data":{"type":"event","title":"PhD Defense by Zhou Fang","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETitle: \u003C\/strong\u003EMachine Learning Enhanced Feature Extraction and Biomarker Identification from Spatial Transcriptomics Data.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EDate:\u0026nbsp;\u003C\/strong\u003EApril 13th, 2026\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETime:\u003C\/strong\u003E\u0026nbsp;1:00pm - 3:00pm\u003C\/p\u003E\u003Cp\u003ELocation: Krone Engineered Biosystems Building (EBB), room 1005, Children\u2019s Healthcare of Atlanta Seminar room (First floor CHOA Room)\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EZoom:\u003C\/strong\u003E\u0026nbsp;\u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/91470654803?pwd=YyPkJ2xSurahERwLQR5tpoeEa7DP4p.1\u0026amp;from=addon\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/91470654803?pwd=YyPkJ2xSurahERwLQR5tpoeEa7DP4p.1\u0026amp;from=addon\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EZhou Fang\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EMachine Learning PhD Student\u003C\/p\u003E\u003Cp\u003EDepartment of Biomedical Engineering\u003Cbr\u003EGeorgia Institute of Technology\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E1 Dr. Ahmet F. Coskun (Advisor), Department of Biomedical Engineering, Georgia Institute of Technology\u003C\/p\u003E\u003Cp\u003E2 Dr. Peng Qiu, Department of Biomedical Engineering, Georgia\u0026nbsp;Institute of Technology\u003C\/p\u003E\u003Cp\u003E3 Dr. Cassie Mitchell, Department of Biomedical Engineering, Georgia Institute of Technology\u003C\/p\u003E\u003Cp\u003E4 Dr. Sara McCoy, Department of Rheumatology, University of Wisconsin, Madison\u003C\/p\u003E\u003Cp\u003E5 Dr. Xiuwei Zhang, School of Computational Science and Engineering, Georgia\u0026nbsp;Institute of Technology\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAdvances in spatial transcriptomics technologies have generated rich molecular data at high spatial resolution, revealing complex spatial organizations of biological samples. Current methods fail to balance capturing data complexity and result interpretability. This thesis presents three graph-based methods aimed at bridging the gap. First, Spatially Resolved Gene Neighborhood Network (SpaGNN) quantifies pairwise subcellular colocalization relationships among genes, producing spatially resolved features that outperform single-cell ribonucleic acid (RNA) expression in distinguishing similar cells. Second, 3-Dimensional Spatially Resolved Gene Neighborhood Network with Embedding (3D-SpaGNN-E) extends the SpaGNN pipeline to 3D spatial transcriptomics data and introduces a graph autoencoder to model relationships among subcellular regions, enabling the identification of cell-cell communication sites. The last part applies a graph attention network to characterize cellular neighborhoods in subtypes of Sj\u00f6gren\u2019s disease, learning a disease-relevant latent representation. Analysis of the latent space identified distinct cellular neighborhoods and gene expression associated with disease states. Together, these approaches represent a suite of graph-based frameworks for analyzing the spatial organization of biological samples while maintaining interpretability.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EMachine Learning Enhanced Feature Extraction and Biomarker Identification from Spatial Transcriptomics Data\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Machine Learning Enhanced Feature Extraction and Biomarker Identification from Spatial Transcriptomics Data"}],"uid":"27707","created_gmt":"2026-04-02 18:27:17","changed_gmt":"2026-04-02 18:27:44","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-04-13T13:00:00-04:00","event_time_end":"2026-04-13T15:00:00-04:00","event_time_end_last":"2026-04-13T15:00:00-04:00","gmt_time_start":"2026-04-13 17:00:00","gmt_time_end":"2026-04-13 19:00:00","gmt_time_end_last":"2026-04-13 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Krone Engineered Biosystems Building (EBB), room 1005, Children\u2019s Healthcare of Atlanta Seminar room (First floor CHOA Room)","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}