{"683601":{"#nid":"683601","#data":{"type":"event","title":"Federated Causal Learning for Distributed Manufacturing Networks","body":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/users\/nagi-gebraeel\u0022\u003ENagi Gebraeel\u003C\/a\u003E\u003Cbr\u003EGeorgia Power Early Career Professor\u003Cbr\u003EH. Milton Stewart School of Industrial and Systems Engineering\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ETuesday, August 26\u003C\/strong\u003E\u003Cbr\u003E12 \u2013 1 p.m.\u003Cbr\u003ELocation: Callaway\/GTMI bldg.,\u003Cbr\u003ERoom 114\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003ELunch provided for in-person attendees on a first come first serve basis.\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003EIf you can\u2019t join us in-person, \u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/99956204656?pwd=VfCXudca58YerAGtGstWqBLB7kgZrM.1 \u0022\u003Ejust us virtually via Zoom\u003C\/a\u003E.\u003C\/p\u003E\u003Ch3\u003E\u003Ca href=\u0022https:\/\/www.eventbrite.com\/e\/gtmi-lunch-learn-lecture-series-fall-2025-nagi-gebraeel-tickets-1438182415319?aff=oddtdtcreator\u0022\u003EWhether you are joining virtually or in person, please register here prior to attending.\u003C\/a\u003E\u003C\/h3\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract:\u003C\/strong\u003E Industry 4.0 has transformed geographically distributed manufacturing enterprises into digitally interconnected networks. This shift has introduced significant challenges in maintaining operational efficiency and managing process disruptions across networked sites. Traditional analytics struggle in this environment because collecting and centralizing high-frequency sensor data from multiple facilities places heavy demands on bandwidth and latency, while differences in local control systems add further complexity and heterogeneity. Decentralized machine-learning frameworks, such as Federated Learning (FL), help mitigate these challenges by enabling sites to collaboratively train shared models without exchanging raw data. However, conventional FL approaches still fall short of capturing how disturbances at one site reverberate through the broader network. \u0026nbsp;In this talk, I will introduce a new methodology that addresses this limitation by uncovering interdependencies across heterogeneous operations at different sites. Using a federated form of Granger causality, our approach enables each local controller not only to diagnose its own equipment but also to reason about upstream and downstream effects across sites. By capturing these cross-site relationships, the framework supports more effective process optimization, accelerates root-cause analysis, and enhances cybersecurity resilience.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESpeaker Bio:\u003C\/strong\u003E Professor Nagi Gebraeel is the Georgia Power Early Career Professor in the\u0026nbsp;Stewart School of Industrial and Systems Engineering\u202fat Georgia Tech.\u0026nbsp; Dr. Gebraeel\u2019s research sits at the nexus of industrial analytics, machine learning, and decision-making under uncertainty. He develops advanced statistical and causal-learning algorithms for machine diagnostics and prognostics, as well as optimization models that guide subsequent operational and logistical decisions in capital-intensive sectors, such as manufacturing, power generation, and aerospace. Dr. Gebraeel leads the Predictive Analytics and Intelligent Systems (PAIS) research group in ISyE. He is a Fellow of the Institute of Industrial and Systems Engineers and was the former president of its Quality and Reliability Engineering Division.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGTMI Lunch and Learn Lecture Series: Nagi Gabraeel, Georgia Tech\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"GTMI Lunch and Learn Lecture Series: Nagi Gebraeel, Georgia Tech"}],"uid":"35575","created_gmt":"2025-08-06 18:10:30","changed_gmt":"2025-08-06 18:17:03","author":"adavidson38","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-08-26T12:00:00-04:00","event_time_end":"2025-08-26T13:00:00-04:00","event_time_end_last":"2025-08-26T13:00:00-04:00","gmt_time_start":"2025-08-26 16:00:00","gmt_time_end":"2025-08-26 17:00:00","gmt_time_end_last":"2025-08-26 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"GTMI Building Rm. 114, 813 Ferst Drive Northwest Atlanta, GA 30332","extras":[],"groups":[{"id":"155831","name":"Georgia Tech Manufacturing Institute (GTMI)"}],"categories":[],"keywords":[{"id":"189814","name":"go-researchevents"},{"id":"186857","name":"go-gtmi"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:mcull3@gatech.edu\u0022\u003EMadeleine Cull\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}