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        "date_start":"2026-11-05",
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        "event_title":"Cosmo Whyte: Under the Quiet, Beyond the Eye",
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        "combined_title":"Cosmo Whyte: Under the Quiet, Beyond the Eye",
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        "event_type":"Exhibition",
        "event_type_id":"7",
        "description":"Curated by Srimoyee Mitra\n\nStamps Gallery kicks off the fall 2026 semester with an ambitious mid-career survey of interdisciplinary artist Cosmo Whyte. Born and raised in Jamaica, Whyte completed a BFA from Bennington College and earned an MFA from the University of Michigan. He is currently a faculty member at the School of the Arts and Architecture, UCLA.\n\nThis exhibition brings together two central concerns that animate Whyte\u2019s artistic practice: the archive, both personal and public, as a site of disturbance; and migration as a lived experience of refuge, refusal, and reinvention. In Whyte\u2019s work, the archive is never static or neutral. Rather, it is a contested space where official histories encounter memory, inheritance, and the fragments of stories carried across generations. His practice moves within this charged interstitial terrain, between what has been recorded and what has been remembered, between institutional knowledge and embodied experience. Whyte invites the viewer to consider the fluidity of geographic borders and layered cultural identities that have persisted despite societal unrest caused by racial and socio-economic hierarchies across generations. In an era of intensified border politics and renewed debates over national identity, Whyte\u2019s work offers a timely meditation on memory, movement, and belonging.\n\nPresented with support from the U-M Institute for Humanities, the U-M LSA Center for Latin American and Caribbean Studies, and the U-M Library.",
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        "location_name":"Stamps Gallery, 201 South Division Street Ann Arbor, Michigan 48104",
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        "tags":["Art"],
        "website":"https:\/\/stamps.umich.edu\/events\/cosmo-whyte-under-the-quiet-beyond-the-eye",
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    {
        "datetime_modified":"20261001T140744",
        "datetime_start":"20261105T120000",
        "datetime_end":"20261105T130000",
        "has_end_time":1,
        "date_start":"2026-11-05",
        "date_end":"2026-11-05",
        "time_start":"12:00:00",
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        "time_zone":"America\/Detroit",
        "event_title":"DCMB Tools and Technology Seminar by Binh Duong Giap (Ophthalmology & Visual Sciences)",
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        "combined_title":"DCMB Tools and Technology Seminar by Binh Duong Giap (Ophthalmology & Visual Sciences): \u201cAdvancing Cataract Surgery Analytics with AI: Pupil Segmentation and Surgical Skill Metrics\u201d",
        "event_subtitle":"\u201cAdvancing Cataract Surgery Analytics with AI: Pupil Segmentation and Surgical Skill Metrics\u201d",
        "event_type":"Workshop \/ Seminar",
        "event_type_id":"21",
        "description":"Join us for the DCMB Tools & Technology Seminar Series featuring a presentation by Binh Duong Giap from the Department of Ophthalmology & Visual Sciences. Enjoy a complimentary pizza lunch while learning about innovative research and cutting-edge tools.\n\n\u201cAdvancing Cataract Surgery Analytics with AI: Pupil Segmentation and Surgical Skill Metrics\u201d\n\nAbstract:  \nThe growing availability of surgical video data creates opportunities to develop computational tools for automated analysis of surgical procedures. In cataract surgery, quantitative analysis of intraoperative videos can support research, surgical training, and objective assessment of surgical performance. However, extracting reliable visual features from surgical videos remains challenging due to instrument occlusion, lighting variations, and complex surgical motion.\n\nIn this seminar, I will present a computational framework for automated analysis of cataract surgery videos. First, I introduce tensor-based feature extraction methods for robust pupil recognition and segmentation during surgery. These methods enable reliable detection of pupil structures under challenging intraoperative conditions. I will also present CatSkill, an AI-based system that analyzes surgical videos to derive quantitative metrics for assessing surgical skill. Together, these approaches demonstrate how computer vision and machine learning can enable objective analysis of surgical videos and support the development of data-driven tools for ophthalmic surgery.",
        "occurrence_notes":"MS1 B-Wing",
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        "location_name":"Medical Science Unit I",
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        "tags":["Basic Science","Bioinformatics","Biology","Life Science"],
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