{"690761":{"#nid":"690761","#data":{"type":"event","title":"PhD Defense by Jacob N. Vagott","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EJacob N. Vagott\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAdvisor: Prof. Karl Jacob\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003Ewill propose a doctoral thesis entitled,\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EManufacturing-Aware Deviation Encoding for Robust Inverse Design of Additively Manufactured Lattice Metamaterials\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EOn\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EFriday, June 26th, 2026\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E1:00 pm EST\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003EZoom Link: \u003C\/em\u003E\u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fgatech.zoom.us%2Fj%2F98511662676\u0026amp;data=05%7C02%7Cfkhan47%40gatech.edu%7C1c3558de3b4942b9998508decbaf0f1f%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639172149879904715%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=cADwVC849vW9wF0UVFfdPqchxW%2BKEjBguT%2B121zqofs%3D\u0026amp;reserved=0\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/gatech.zoom.us\/j\/98511662676. Click or tap if you trust this link.\u0022\u003E\u003Cem\u003Ehttps:\/\/gatech.zoom.us\/j\/98511662676\u003C\/em\u003E\u003C\/a\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EAdditive manufacturing (AM) of lattice metamaterials enables fabrication of diverse structures with highly tunable mechanical responses, but process-induced geometric deviations and variability create uncertainty when comparing as-fabricated performance to predictions. Conventional inverse design and topology optimization frameworks often assume ideal reproductions of as-designed geometries, while methods that address uncertainty often treat manufacturing variability as stochastic noise to be managed probabilistically rather than as structured geometric information to be directly encoded. As a result, current workflows struggle to deliver robust, uncertainty-aware designs where predicted properties remain accurate under real process variability. This dissertation introduces the Manufacturing-Aware Deviation Encoding (MADE) vector: a compact, empirically-derived descriptor that encodes the process-specific geometric deviation fingerprint, which can be embedded directly into surrogate modeling and the inverse design loop. MADE is derived from a minimal set of CT-extracted geometric deviation features that explain dominant variance in mechanical performance over a range of lattice geometries. Demonstrated on fused filament fabrication (FFF)-printed thermoplastic polyurethane (TPU) re-entrant auxetic lattice samples, this framework enables surrogate models that propagate manufacturing uncertainty through the inverse design loop, helping bridge the gap between computational design intent and reality.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ECommittee\u003C\/strong\u003E\u003C\/p\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli data-list-item-id=\u0022ee899613368c2998b1c177322c2ed64be\u0022\u003EProf. Karl Jacob \u2013 School of Materials Science and Engineering (advisor)\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli data-list-item-id=\u0022edd028279ca0fa2dd63e6f028a6f12315\u0022\u003EProf. Hamid Garmestani \u2013 School of Materials Science and Engineering\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli data-list-item-id=\u0022e62fd120f6c07e5f699183a2a1d7e156f\u0022\u003EProf. Donggang Yao \u2013 School of Materials Science and Engineering\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cul type=\u0022disc\u0022\u003E\u003Cli data-list-item-id=\u0022eda2ae5434b5ed15facfca9e6a3d1eedf\u0022\u003EProf. Seyed M. Ghiaasiaan - School of Mechanical Engineering\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EManufacturing-Aware Deviation Encoding for Robust Inverse Design of Additively Manufactured Lattice Metamaterials\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Manufacturing-Aware Deviation Encoding for Robust Inverse Design of Additively Manufactured Lattice Metamaterials"}],"uid":"36872","created_gmt":"2026-06-16 17:10:42","changed_gmt":"2026-06-17 14:32:55","author":"fkhan47","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-06-26T13:00:56-04:00","event_time_end":"2026-06-26T15:00:56-04:00","event_time_end_last":"2026-06-26T15:00:56-04:00","gmt_time_start":"2026-06-26 17:00:56","gmt_time_end":"2026-06-26 19:00:56","gmt_time_end_last":"2026-06-26 19:00:56","rrule":null,"timezone":"America\/New_York"},"extras":[],"related_links":[{"url":"https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fgatech.zoom.us%2Fj%2F98511662676\u0026data=05%7C02%7Cfkhan47%40gatech.edu%7C1c3558de3b4942b9998508decbaf0f1f%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639172149879904715%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026sdata=cADwVC849vW9wF0UVFfdPqchxW%2BKEjBguT%2B121zqofs%3D\u0026reserved=0","title":"Zoom"}],"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":""}}}