{"692582":{"#nid":"692582","#data":{"type":"event","title":"ISyE Picture Day","body":[{"value":"\u003Cp\u003EPhotos will be taking place over the course of three days in the Cecil G. Johnson ISyE Studio, located on the 5th floor of George Tower, Room 509.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EIf you cannot make your assigned group day, please feel free to come by on any operating date below:\u0026nbsp;\u003C\/p\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e2f1b1687a48ae09269c373bbf3195d6c\u0022\u003ETime: 10:00AM - 3:00PM\u003C\/li\u003E\u003Cli data-list-item-id=\u0022ebe4d4b1a7ede4ed269b1d9d500942c50\u0022\u003EDates:\u0026nbsp;\u003Cul\u003E\u003Cli data-list-item-id=\u0022eb92a8beffb5e48db833dd313b7942251\u0022\u003E10\/6: Staff\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e5dee79ba5c87a39359f21fa66d3de8f1\u0022\u003E10\/7: Faculty\u003C\/li\u003E\u003Cli data-list-item-id=\u0022ed9d8af57493a095325579e2617c11c8e\u0022\u003E10\/8: Ph.D. Students\u003C\/li\u003E\u003C\/ul\u003E\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003E\u003Cstrong\u003ERecommendations for attire:\u0026nbsp;\u003C\/strong\u003E\u003C\/p\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e90491806f3730e225bbb25f12317605e\u0022\u003EWear blue, or dark-colored clothing (will be on a white backdrop)\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e4ed83ec08e0e8707783589f8aa1bc151\u0022\u003EDo NOT wear red\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e836c8b8558156d20fee019e920b1a84d\u0022\u003EAvoid wearing large jewelry and patterns\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPhotos will be taking place over the course of three days in the Cecil G. Johnson ISyE Studio\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Photos will be taking place over the course of three days in the Cecil G. Johnson ISyE Studio"}],"uid":"36760","created_gmt":"2026-09-14 14:46:09","changed_gmt":"2026-09-14 14:55:03","author":"jsmith830","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-06T10:00:29-04:00","event_time_end":"2026-10-08T15:00:00-04:00","event_time_end_last":"2026-10-08T15:00:00-04:00","gmt_time_start":"2026-10-06 14:00:29","gmt_time_end":"2026-10-08 19:00:00","gmt_time_end_last":"2026-10-08 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Cecil G. Johnson Studio, George Tower, Room 509","extras":[],"hg_media":{"681143":{"id":"681143","type":"image","title":"ISyE Picture Day 2026","body":"\u003Cp\u003EISyE Picture Day 2026\u003C\/p\u003E","created":"1789397567","gmt_created":"2026-09-14 14:52:47","changed":"1789397567","gmt_changed":"2026-09-14 14:52:47","alt":"ISyE Picture Day 2026","file":{"fid":"265504","name":"Picture-Day2.jpg","image_path":"\/sites\/default\/files\/2026\/09\/14\/Picture-Day2.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/14\/Picture-Day2.jpg","mime":"image\/jpeg","size":242420,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/14\/Picture-Day2.jpg?itok=ejalCeMv"}}},"media_ids":["681143"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692581":{"#nid":"692581","#data":{"type":"event","title":"ISYE Statistics Seminar - Alon Kipnis","body":[{"value":"\u003Cdiv dir=\u0022ltr\u0022\u003E\u003Cdiv\u003E\u003Cstrong\u003ETitle\u003C\/strong\u003E: The Sharp Minimax Risk for High-Dimensional Uniformity Testing and Applications to Model Calibration\u003Cbr\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract\u003C\/strong\u003E:\u0026nbsp;Testing whether high-dimensional categorical data follow a specified distribution is a fundamental problem in statistics, learning, and theoretical computer science.\u0026nbsp;We derive an expression for the asymptotic minimax risk in terms of the number of categories, the sample size, and the separation between the alternative class and the uniform distribution null. This result settles an open problem related to identity and uniformity testing in computer science and nonparametric hypothesis testing on distributions in mathematical statistics.\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EThe sharp characterization enables comparison among competing tests at the level of exact constants rather than asymptotic rates, revealing differences invisible under standard sample-complexity analyses.\u0026nbsp;Interestingly, commonly used chi-squared and collision statistics are asymptotically minimax under fixed sample sizes but fail to retain this property under Poisson sampling. We derive a new statistic that is asymptotically minimax in both settings.\u0026nbsp;The proof combines ideas from signal detection in white noise\u0026nbsp;with a new conditional central limit theorem that overcomes the de-Poissonization challenge.\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EAs a practical consequence, the sharp constant answers a longstanding design question in calibration testing:\u003C\/div\u003E\u003Cdiv\u003E\u003Cstrong\u003EHow many bins should one use when testing calibration using the probability integral transform\u003C\/strong\u003E?\u003C\/div\u003E\u003Cdiv\u003EWe derive an explicit formula for the largest number of bins that guarantees a prescribed minimax risk, replacing heuristic bin selection by a statistically optimal design rule.\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EThis talk is partly based on the following work, which received the best non-student paper award in an\u0026nbsp;AISTATS 2026 workshop.\u003C\/div\u003E\u003Cdiv\u003EA. Kipnis, \u0022Calibrating the Calibration Tester: Optimal Binning and Minimax Calibration Testing for Continuous Predictive Models\u0022,\u0026nbsp;\u003Cem\u003ETowards Trustworthy Predictions: Theory and Applications of Calibration for Modern AI\u0026nbsp;@ AISTATS 2026\u003C\/em\u003E (\u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fopenreview.net%2Fforum%3Fid%3Ddy7XNC3W0g\u0026amp;data=05%7C02%7Cstatseminarseries%40isye.gatech.edu%7C9ebe7f175dc64f41f90008df125ceb18%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639249862490750398%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=bxxTY8NVzHEo9fKT4%2Bt44d%2FH6NN4Z3N%2FuHrmGsvmJ1Y%3D\u0026amp;reserved=0\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/openreview.net\/forum?id=dy7XNC3W0g. Click or tap if you trust this link.\u0022\u003Ehttps:\/\/openreview.net\/forum?id=dy7XNC3W0g\u003C\/a\u003E)\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cstrong\u003EBio\u003C\/strong\u003E:\u0026nbsp;Alon Kipnis is a Senior Lecturer (Assistant Professor) at the Efi Arazi School of Computer Science, Reichman University, Israel. He received the Ph.D. in Electrical Engineering from Stanford University in 2017, and was a Koret Foundation Postdoctoral Fellow in Statistics at Stanford University from 2018 to 2021.\u0026nbsp;His research focuses on mathematical statistics, information theory, signal processing, and machine learning.\u0026nbsp;\u003C\/div\u003E\u003Cp\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cdiv\u003ETesting whether high-dimensional categorical data follow a specified distribution is a fundamental problem in statistics, learning, and theoretical computer science.\u0026nbsp;We derive an expression for the asymptotic minimax risk in terms of the number of categories, the sample size, and the separation between the alternative class and the uniform distribution null. This result settles an open problem related to identity and uniformity testing in computer science and nonparametric hypothesis testing on distributions in mathematical statistics.\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EThe sharp characterization enables comparison among competing tests at the level of exact constants rather than asymptotic rates, revealing differences invisible under standard sample-complexity analyses.\u0026nbsp;Interestingly, commonly used chi-squared and collision statistics are asymptotically minimax under fixed sample sizes but fail to retain this property under Poisson sampling. We derive a new statistic that is asymptotically minimax in both settings.\u0026nbsp;The proof combines ideas from signal detection in white noise\u0026nbsp;with a new conditional central limit theorem that overcomes the de-Poissonization challenge.\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003E\u003Cbr\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EAs a practical consequence, the sharp constant answers a longstanding design question in calibration testing:\u003C\/div\u003E\u003Cdiv\u003E\u003Cstrong\u003EHow many bins should one use when testing calibration using the probability integral transform\u003C\/strong\u003E?\u003C\/div\u003E\u003Cdiv\u003EWe derive an explicit formula for the largest number of bins that guarantees a prescribed minimax risk, replacing heuristic bin selection by a statistically optimal design rule.\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EThis talk is partly based on the following work, which received the best non-student paper award in an\u0026nbsp;AISTATS 2026 workshop.\u003C\/div\u003E\u003Cdiv\u003EA. Kipnis, \u0022Calibrating the Calibration Tester: Optimal Binning and Minimax Calibration Testing for Continuous Predictive Models\u0022,\u0026nbsp;\u003Cem\u003ETowards Trustworthy Predictions: Theory and Applications of Calibration for Modern AI\u0026nbsp;@ AISTATS 2026\u003C\/em\u003E (\u003Ca href=\u0022https:\/\/nam12.safelinks.protection.outlook.com\/?url=https%3A%2F%2Fopenreview.net%2Fforum%3Fid%3Ddy7XNC3W0g\u0026amp;data=05%7C02%7Cstatseminarseries%40isye.gatech.edu%7C9ebe7f175dc64f41f90008df125ceb18%7C482198bbae7b4b258b7a6d7f32faa083%7C1%7C0%7C639249862490750398%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C\u0026amp;sdata=bxxTY8NVzHEo9fKT4%2Bt44d%2FH6NN4Z3N%2FuHrmGsvmJ1Y%3D\u0026amp;reserved=0\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022 title=\u0022Original URL: https:\/\/openreview.net\/forum?id=dy7XNC3W0g. Click or tap if you trust this link.\u0022\u003Ehttps:\/\/openreview.net\/forum?id=dy7XNC3W0g\u003C\/a\u003E)\u003C\/div\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"The Sharp Minimax Risk for High-Dimensional Uniformity Testing and Applications to Model Calibration"}],"uid":"36868","created_gmt":"2026-09-14 13:59:05","changed_gmt":"2026-09-14 14:14:46","author":"mferrick3","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-30T11:00:00-04:00","event_time_end":"2026-09-30T12:00:00-04:00","event_time_end_last":"2026-09-30T12:00:00-04:00","gmt_time_start":"2026-09-30 15:00:00","gmt_time_end":"2026-09-30 16:00:00","gmt_time_end_last":"2026-09-30 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 1502 ","extras":[],"hg_media":{"681142":{"id":"681142","type":"image","title":"Alon Kipnis","body":null,"created":"1789394934","gmt_created":"2026-09-14 14:08:54","changed":"1789394934","gmt_changed":"2026-09-14 14:08:54","alt":"Alon Kipnis","file":{"fid":"265503","name":"kipnis-13831.jpg","image_path":"\/sites\/default\/files\/2026\/09\/14\/kipnis-13831.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/14\/kipnis-13831.jpg","mime":"image\/jpeg","size":15563,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/14\/kipnis-13831.jpg?itok=iqDz1dMH"}}},"media_ids":["681142"],"groups":[{"id":"660404","name":"ISyE Extended Reality Makerspace (ISYE XR)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692576":{"#nid":"692576","#data":{"type":"event","title":"ISyE Student Seminar Series - Nicholas Sovich","body":[{"value":"\u003Ch2\u003EFlying First-Class on Analytics: Predicting Airline Employee \u0022Standby\u0022 Probabilities\u200b\u003C\/h2\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EFormer Delta data scientist Nick Sovich introduces SCORPION, a machine learning model that predicts standby boarding probabilities for nearly 500,000 Delta flights up to four months in advance. \u200b\u003Cbr\u003E\u003Cbr\u003EBuilt from his experience on 500+ standby flights, SCORPION continuously retrains on historical outcomes and is now used by thousands of Delta employees.\u200b\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Ch2\u003EFlying First-Class on Analytics: Predicting Airline Employee \u0022Standby\u0022 Probabilities\u200b09\/16\/2026\u003C\/h2\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Flying First-Class on Analytics: Predicting Airline Employee \u0022Standby\u0022 Probabilities\u200b"}],"uid":"27764","created_gmt":"2026-09-11 20:55:01","changed_gmt":"2026-09-11 20:57:15","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-16T16:00:00-04:00","event_time_end":"2026-09-16T17:00:00-04:00","event_time_end_last":"2026-09-16T17:00:00-04:00","gmt_time_start":"2026-09-16 20:00:00","gmt_time_end":"2026-09-16 21:00:00","gmt_time_end_last":"2026-09-16 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"GeorgeTower 1102\u200b","extras":[],"hg_media":{"681141":{"id":"681141","type":"image","title":"ISyE Student Seminar Series - Nicholas Sovich","body":null,"created":"1789160180","gmt_created":"2026-09-11 20:56:20","changed":"1789160180","gmt_changed":"2026-09-11 20:56:20","alt":"ISyE Student Seminar Series - Nicholas Sovich","file":{"fid":"265501","name":"sovich-13813.png","image_path":"\/sites\/default\/files\/2026\/09\/11\/sovich-13813.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/11\/sovich-13813.png","mime":"image\/png","size":164566,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/11\/sovich-13813.png?itok=nM-l6AIS"}}},"media_ids":["681141"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"691926":{"#nid":"691926","#data":{"type":"event","title":"Fall 2026 IISE Career Fair","body":[{"value":"\u003Cp\u003EConnect and recruit top-tier talent from the \u003Cstrong\u003E#1 ranked Industrial Engineering program in the nation\u003C\/strong\u003E, and engage with students who are driven, analytical, and ready to make an impact.\u003C\/p\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Ch3\u003EWhy should you attend the IISE Career Fair?\u0026nbsp;\u003C\/h3\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e9f61e32b6bd6ed725723bc361b8d7f2e\u0022\u003E\u003Cstrong\u003ERecruit \u003C\/strong\u003Efor internship and full-time roles across Consulting, Data Analytics, Supply Chain, Operations, Finance, Computer Science, Statistics and more\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e5b4fe49bc5af8830189d93019438a84f\u0022\u003E\u003Cstrong\u003EEngage in a targeted recruiting environment\u003C\/strong\u003E with students primarily from the \u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/about\/school\/facts-rankings\u0022 rel=\u0022noopener noreferrer\u0022 target=\u0022_blank\u0022\u003E\u003Cstrong\u003EH. Milton Stewart School of Industrial and\u0026nbsp;Systems Engineering\u003C\/strong\u003E\u003C\/a\u003E (the event is also publicized to the larger GT community).\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e97e9041cae50bfdefc8c3e90a6ebd4eb\u0022\u003E\u003Cstrong\u003EIncrease visibility\u003C\/strong\u003E and build your organization\u2019s brand at Georgia Tech to recruit in the future.\u0026nbsp;\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Tech\u2019s largest Industrial Engineering Career Fair will take place on Monday, September 21st, 2026 at the Georgia Tech Exhibition Hall.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Tech\u2019s largest Industrial Engineering Career Fair will take place on Monday, September 21st, 2026 at the Georgia Tech Exhibition Hall."}],"uid":"36760","created_gmt":"2026-08-24 18:50:17","changed_gmt":"2026-09-11 16:47:47","author":"jsmith830","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-21T09:00:00-04:00","event_time_end":"2026-09-21T15:00:00-04:00","event_time_end_last":"2026-09-21T15:00:00-04:00","gmt_time_start":"2026-09-21 13:00:00","gmt_time_end":"2026-09-21 19:00:00","gmt_time_end_last":"2026-09-21 19:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Exhibition Hall","extras":[],"hg_media":{"680968":{"id":"680968","type":"image","title":"Fall 2026 IISE Career Fair","body":"\u003Ch3\u003EFall 2026 IISE Career Fair\u003C\/h3\u003E","created":"1787597630","gmt_created":"2026-08-24 18:53:50","changed":"1787597630","gmt_changed":"2026-08-24 18:53:50","alt":"Fall 2026 IISE Career Fair","file":{"fid":"265309","name":"F26-Student-Flyer.jpg","image_path":"\/sites\/default\/files\/2026\/08\/24\/F26-Student-Flyer.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/08\/24\/F26-Student-Flyer.jpg","mime":"image\/jpeg","size":829454,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/08\/24\/F26-Student-Flyer.jpg?itok=tzar8uRM"}}},"media_ids":["680968"],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"691630":{"#nid":"691630","#data":{"type":"event","title":"Techlanta 2026","body":[{"value":"\u003Cdiv\u003E\u003Cdiv\u003E\u003Cp\u003EPresented by Georgia Tech, the Applied AI and VR\/AR Associations, and leading partners across industry, academia, and innovation.\u003C\/p\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cdiv\u003E\u003Cdiv\u003E\u003Cp\u003EThe Georgia Institute of Technology, the Applied AI Association (AAIA), and the VR\/AR Association (VRARA) invite you to Techlanta 2026: Driving the Future of AI, XR, and Global Innovation.\u003C\/p\u003E\u003Cp\u003EJoin us for a curated day of featured presentations, expert discussions, real-world use cases, demonstrations, and tours highlighting AI, XR and spatial computing, robotics, digital twins, advanced manufacturing, human-centered systems engineering, and other emerging technologies.\u003C\/p\u003E\u003Cp\u003EConnect with leaders across enterprise, startups, academia, research, investment, workforce development, and the broader innovation ecosystem. Explore commercialization opportunities, research partnerships, emerging talent, and practical applications shaping the future of intelligent, immersive, and scalable technology.\u003C\/p\u003E\u003Cp\u003ETechlanta is organized in collaboration with Georgia Tech OIT, the new Allen\u2013Davidson\u2013Coleman XR Makerspace, the H. Milton Stewart School of Industrial and Systems Engineering (ISyE), and the Symbiotic and Augmented Intelligence Laboratory (SAIL).\u003C\/p\u003E\u003Cp\u003EThis year\u2019s program will include:\u003C\/p\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e3945ff024a5d1da33d4a465c31296027\u0022\u003Ekeynote and featured presentations\u003C\/li\u003E\u003Cli data-list-item-id=\u0022eb76cf86b5868cdcba064d3043cda88ab\u0022\u003Eexpert panels and interactive discussions\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e0e303f93ec0bbb191d482b09920672c2\u0022\u003Ecurated exhibits and live technology demonstrations\u003C\/li\u003E\u003Cli data-list-item-id=\u0022ed276f86c8ee2187056b4988cf5258314\u0022\u003Escheduled tours of the Allen\u2013Davidson\u2013Coleman XR Makerspace\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e726c6ede7943fc3375529d81f7a9b874\u0022\u003Eopportunities to connect with Georgia Tech researchers, students, and innovation leaders\u003C\/li\u003E\u003C\/ul\u003E\u003Cp\u003EThe event will be held September 17, 2026, at the Georgia Tech Historic Academy of Medicine. Additional agenda, speaker, sponsor, and event details will be announced as they are confirmed.\u003C\/p\u003E\u003Cp\u003EDon\u2019t miss this opportunity to connect with Atlanta\u2019s innovation ecosystem and help shape the future of AI, XR, robotics, advanced manufacturing, and emerging technology adoption.\u003C\/p\u003E\u003Cp\u003EFor recruiter inclusion, group ticketing, sponsorship inquiries, media passes, or additional information, contact atlanta@thevrara.com\u003C\/p\u003E\u003Cp\u003EWe look forward to seeing you at Techlanta 2026!\u003C\/p\u003E\u003C\/div\u003E\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EDon\u2019t miss this opportunity to connect with Atlanta\u2019s innovation ecosystem and help shape the future of AI, XR, robotics, advanced manufacturing, and emerging technology adoption.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Don\u2019t miss this opportunity to connect with Atlanta\u2019s innovation ecosystem and help shape the future of AI, XR, robotics, advanced manufacturing, and emerging technology adoption."}],"uid":"36760","created_gmt":"2026-08-12 18:44:12","changed_gmt":"2026-09-11 16:47:09","author":"jsmith830","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-17T11:00:32-04:00","event_time_end":"2026-09-17T17:00:32-04:00","event_time_end_last":"2026-09-17T17:00:32-04:00","gmt_time_start":"2026-09-17 15:00:32","gmt_time_end":"2026-09-17 21:00:32","gmt_time_end_last":"2026-09-17 21:00:32","rrule":null,"timezone":"America\/New_York"},"location":"Georgia Tech\u2019s Historic Academy of Medicine","extras":[],"hg_media":{"680846":{"id":"680846","type":"image","title":"Techlanta2026","body":"\u003Cp\u003ETechlanta2026\u003C\/p\u003E","created":"1786560825","gmt_created":"2026-08-12 18:53:45","changed":"1786560825","gmt_changed":"2026-08-12 18:53:45","alt":"Techlanta2026","file":{"fid":"265172","name":"image.jpg","image_path":"\/sites\/default\/files\/2026\/08\/12\/image.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/08\/12\/image.jpg","mime":"image\/jpeg","size":323749,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/08\/12\/image.jpg?itok=nVhlrErT"}}},"media_ids":["680846"],"related_links":[{"url":"https:\/\/www.eventbrite.com\/e\/techlanta-2026-tickets-1993945297059","title":"Register Here"}],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"194681","name":"Exhibit"},{"id":"1789","name":"Conference\/Symposium"},{"id":"194613","name":"Industry"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692148":{"#nid":"692148","#data":{"type":"event","title":"ISyE Seminar - Eugene Feinberg (Stony Brook University)","body":[{"value":"\u003Ch2\u003EInfinite-State Partially Observable Markov Decision Processes with Applications to Inventory Control\u003C\/h2\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EThis talk describes the progress in analysis and optimization of Markov Decision Processes (MDPs) and Partially Observable MDPs (POMDPs) with infinite state spaces and possibly noncompact action sets. We shall also discuss applications to inventory control and to controlled linear Gaussian systems.\u0026nbsp;\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003EEugene A. Feinberg received MS in Applied Mathematics and Computer Engineering from Moscow University of Transportation, Russia, in 1976 and Ph.D. in Probability and Statistics from Vilnius University, Lithuania, in 1979. Currently he is Distinguished Professor at the Department of Applied Mathematics and Statistics of Stony Brook University.\u003Cbr\u003E\u003Cbr\u003EHis research interests include stochastic models of operations research, probability theory, real analysis, Markov Decision Processes, and applications of operations research and statistics to engineering, biology, and medicine. He has published more than 100 papers and edited the Handbook on Markov Decision Processes. His research has been partially supported by the National Science Foundation, Office of Naval Research, National Institute of Health, New York Office of Science, Technology and Academic Research, and private industry. He has served as a Council Member of the INFORMS Applied Probability Society and on several editorial boards. He is a fellow of INFORMS.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EInfinite-State Partially Observable Markov Decision Processes with Applications to Inventory Control\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Infinite-State Partially Observable Markov Decision Processes with Applications to Inventory Control"}],"uid":"36870","created_gmt":"2026-09-01 13:17:13","changed_gmt":"2026-09-10 22:27:03","author":"bjones434","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-16T11:00:00-04:00","event_time_end":"2026-10-16T12:00:00-04:00","event_time_end_last":"2026-10-16T12:00:00-04:00","gmt_time_start":"2026-10-16 15:00:00","gmt_time_end":"2026-10-16 16:00:00","gmt_time_end_last":"2026-10-16 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 1502","extras":[],"hg_media":{"681137":{"id":"681137","type":"image","title":"Eugene Feinberg","body":"\u003Cp\u003EEugene Feinberg\u003C\/p\u003E","created":"1789079191","gmt_created":"2026-09-10 22:26:31","changed":"1789079191","gmt_changed":"2026-09-10 22:26:31","alt":"Eugene Feinberg","file":{"fid":"265497","name":"Eugene-Feinberg.jpg","image_path":"\/sites\/default\/files\/2026\/09\/10\/Eugene-Feinberg.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/10\/Eugene-Feinberg.jpg","mime":"image\/jpeg","size":297630,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/10\/Eugene-Feinberg.jpg?itok=JUB0cw_a"}}},"media_ids":["681137"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692146":{"#nid":"692146","#data":{"type":"event","title":"ISyE Seminar - Eunshin Byon (University of Michigan)","body":[{"value":"\u003Ch2\u003ELearning What Matters: Scalable Offline and Online Calibration of Digital Twins\u003C\/h2\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EDigital twins promise continuous, high-fidelity representations of physical systems, yet their practical deployment is often constrained by the computational cost of simulation and calibration. This talk presents a unified perspective on making digital twin calibration more efficient, adaptive, and scalable by learning where computational effort matters most.\u003Cbr\u003E\u003Cbr\u003EThe first part addresses offline calibration of block-structured models. I introduce a doubly importance-driven calibration method that learns which parameter blocks and which observations are most informative, and directs simulation effort toward the parts of the problem that contribute most to the optimization. This targeted allocation substantially reduces computational cost while preserving calibration accuracy.\u003Cbr\u003E\u003Cbr\u003EThe second part turns to online calibration, where model parameters evolve over time and computational resources are limited. The proposed framework combines fast, edge-side surrogate filtering with periodic, cloud-side discrepancy correction based on high-fidelity simulations. This two-tier architecture enables real-time parameter adaptation while maintaining consistency with the underlying digital twin.\u003Cbr\u003E\u003Cbr\u003ETogether, these methods show how learning what matters\u2014in parameters, observations, and computation\u2014can support digital twins that remain accurate, scalable, and continuously adaptive in practice.\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003EDr. Eunshin Byon is a Professor in the Department of Industrial and Operations Engineering at the University of Michigan, Ann Arbor, where she also serves as Director of the Master\u0027s Program. She received her Ph.D. in Industrial and Systems Engineering from Texas A\u0026amp;M University in 2010. Her research spans data science, digital twin modeling and analysis, and quality and reliability engineering, with applications in energy, healthcare, and manufacturing systems. She served as Chair of the Quality, Statistics, and Reliability (QSR) Section of INFORMS in 2019\u20132020, and her research group has received multiple research and teaching awards from INFORMS, IISE, and IEEE. Dr. Byon is currently a Senior Editor for the INFORMS Journal on Data Science (2024\u2013present) and a Department Editor for IISE Transactions (2021\u2013present). She previously served as an Associate Editor for IISE Transactions (2019\u20132021), the INFORMS Journal on Data Science (2020\u20132024), and IEEE Transactions on Automation Science and Engineering (2019\u20132021).\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearning What Matters: Scalable Offline and Online Calibration of Digital Twins\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Learning What Matters: Scalable Offline and Online Calibration of Digital Twins"}],"uid":"36870","created_gmt":"2026-09-01 12:59:04","changed_gmt":"2026-09-10 22:23:25","author":"bjones434","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-11T11:00:00-04:00","event_time_end":"2026-09-11T12:00:00-04:00","event_time_end_last":"2026-09-11T12:00:00-04:00","gmt_time_start":"2026-09-11 15:00:00","gmt_time_end":"2026-09-11 16:00:00","gmt_time_end_last":"2026-09-11 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 1502","extras":[],"hg_media":{"681136":{"id":"681136","type":"image","title":"Eunshin Byon","body":"\u003Cp\u003EEunshin Byon\u003C\/p\u003E","created":"1789078949","gmt_created":"2026-09-10 22:22:29","changed":"1789078949","gmt_changed":"2026-09-10 22:22:29","alt":"Eunshin Byon","file":{"fid":"265496","name":"Eunshin-Byon.jpg","image_path":"\/sites\/default\/files\/2026\/09\/10\/Eunshin-Byon.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/10\/Eunshin-Byon.jpg","mime":"image\/jpeg","size":83119,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/10\/Eunshin-Byon.jpg?itok=PMUH2M4n"}}},"media_ids":["681136"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692192":{"#nid":"692192","#data":{"type":"event","title":"ISyE Seminar - Omar El Housni (Cornell Tech)","body":[{"value":"\u003Ch2\u003ETwo-sided Assortment Optimization\u003C\/h2\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ETwo-sided matching platforms, including labor markets, dating apps, accommodation services, and ridesharing systems, must make matching decisions in the presence of choice congestion and strategic platform design challenges. When agents have correlated preferences, popular options can attract too much demand, reduce overall efficiency, and lead to poor market outcomes. In this\u0026nbsp;talk, I will present a framework for two-sided assortment optimization that studies how a platform should decide which options to display to agents and in what order, with the goal of improving matching performance. The main focus will be on maximizing the expected number of matches under general choice models. I will describe several natural classes of platform policies, ranging from static simultaneous displays to fully adaptive sequential policies, and compare their power through adaptivity gap results. I will also discuss polynomial-time approximation algorithms for computing near-optimal policies, and then briefly discuss the revenue-maximization version of the problem, where matches generate pair-dependent rewards. This\u0026nbsp;talk\u0026nbsp;is based on joint works with Alfredo Torrico, Ulysse Hennebelle, and Mohammadreza Ahmadnejadsaein.\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003EOmar El Housni is an Assistant Professor in the School of Operations Research and Information Engineering at Cornell Tech and Cornell University. He is a Field Member of the Center of Applied Mathematics at Cornell. He is also an Amazon Scholar. His research focuses on decision-making under uncertainty where he aims to develop optimization models and design robust and efficient algorithms to address a wide range of operational problems, including revenue management problems such as assortment optimization and online matchings. Omar has spent time as a research scientist at Amazon and Uber where he contributed to the design and implementation of data-driven optimization models for matching and retailing platforms. Omar holds a PhD in Operations Research from Columbia University and an MS and BS in Applied Mathematics from Ecole Polytechnique (Paris). His work has been recognized by INFORMS George Nicholson award and his current research is supported by NSF.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ETwo-sided Assortment Optimization\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Two-sided Assortment Optimization "}],"uid":"36870","created_gmt":"2026-09-02 13:00:42","changed_gmt":"2026-09-09 23:12:57","author":"bjones434","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-02T11:00:00-04:00","event_time_end":"2026-10-02T12:00:00-04:00","event_time_end_last":"2026-10-02T12:00:00-04:00","gmt_time_start":"2026-10-02 15:00:00","gmt_time_end":"2026-10-02 16:00:00","gmt_time_end_last":"2026-10-02 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 1502","extras":[],"hg_media":{"681114":{"id":"681114","type":"image","title":"Omar El Housni","body":null,"created":"1788995524","gmt_created":"2026-09-09 23:12:04","changed":"1788995524","gmt_changed":"2026-09-09 23:12:04","alt":"Omar El Housni","file":{"fid":"265473","name":"el-housni-13725.jpg","image_path":"\/sites\/default\/files\/2026\/09\/09\/el-housni-13725.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/09\/el-housni-13725.jpg","mime":"image\/jpeg","size":191001,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/09\/el-housni-13725.jpg?itok=ELzkHJ7h"}}},"media_ids":["681114"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692468":{"#nid":"692468","#data":{"type":"event","title":"ISyE Seminar - Jian Kang (University of Michigan)","body":[{"value":"\u003Ch2\u003EModern Gaussian Processes for Neuroimaging Data Analysis\u003C\/h2\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003ERecent advances in neuroimaging have produced massive and heterogeneous datasets, ranging from fMRI with high spatial resolution to EEG with high temporal resolution, characterized by complex spatiotemporal correlations and substantial inter-subject variability. Traditional regression models and Gaussian process (GP) approaches with fixed parametric kernels often fail to model such complex data effectively while maintaining scalability and interpretability. This talk introduces a family of modern Bayesian GP frameworks that integrate deep kernel learning, neural network priors, and geometric modeling for large-scale neuroimaging analysis. An example is the Deep Kernel Learning Process (DKLP), which embeds deep neural networks within GP priors to learn data-adaptive covariance structures directly from imaging data. DKLP provides a unified modeling foundation for image-on-scalar, scalar-on-image, and image-on-image regression, supported by theoretical guarantees and efficient posterior computation. Applications to fMRI data from the Adolescent Brain Cognitive Development (ABCD) study reveal reproducible cortical activation patterns associated with cognitive ability, while analyses of EEG-based brain\u2013computer interface data demonstrate robust neural decoding under high noise. I will also discuss scalable heat-kernel GPs on manifolds and thresholded GP\u2013based spatially varying neural network priors, which together expand the scope of Bayesian inference for complex neuroimaging data.\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003EDr. Jian Kang is Professor and Associate Chair for Research in the Department of Biostatistics at the University of Michigan. His research lies at the intersection of Bayesian statistics, machine learning, and artificial intelligence, with applications in neuroimaging, brain\u2013computer interfaces, omics, and precision medicine. He has published more than 175 papers in leading statistics, machine learning, and biomedical journals. Dr. Kang has served as an Associate Editor for several premier statistical journals, including the Journal of the American Statistical Association (JASA), The Annals of Applied Statistics (AOAS) and Biometrics. He is a Fellow of both the Institute of Mathematical Statistics (IMS) and the American Statistical Association (ASA). He currently serves as Chair of the ASA Section on Statistics in Imaging.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EModern Gaussian Processes for Neuroimaging Data Analysis\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Modern Gaussian Processes for Neuroimaging Data Analysis "}],"uid":"36870","created_gmt":"2026-09-09 18:46:28","changed_gmt":"2026-09-09 23:08:24","author":"bjones434","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-25T11:00:00-04:00","event_time_end":"2026-09-25T12:00:00-04:00","event_time_end_last":"2026-09-25T12:00:00-04:00","gmt_time_start":"2026-09-25 15:00:00","gmt_time_end":"2026-09-25 16:00:00","gmt_time_end_last":"2026-09-25 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 1502","extras":[],"hg_media":{"681113":{"id":"681113","type":"image","title":"Jian Kang","body":null,"created":"1788995256","gmt_created":"2026-09-09 23:07:36","changed":"1788995256","gmt_changed":"2026-09-09 23:07:36","alt":"Jian Kang","file":{"fid":"265472","name":"kang-13747.jpg","image_path":"\/sites\/default\/files\/2026\/09\/09\/kang-13747.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/09\/kang-13747.jpg","mime":"image\/jpeg","size":428535,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/09\/kang-13747.jpg?itok=r9JNvQuS"}}},"media_ids":["681113"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692469":{"#nid":"692469","#data":{"type":"event","title":"ISyE Seminar - Judy Jin (University of Michigan)","body":[{"value":"\u003Ch2\u003EAI-Enabled In-Situ Quality Control: Learning Beyond the Known\u003C\/h2\u003E\u003Cp\u003E\u003Cbr\u003E\u003Cstrong\u003EAbstract: \u003C\/strong\u003EModern manufacturing generates increasingly rich in-situ sensing data, creating new opportunities for AI to enable automated and intelligent quality control decisions. However, conventional quality control using supervised learning relies on abundant labeled data and assumes that future product defects or process faults resemble those known during training. In practice, new defect types emerge, while abnormal conditions may be rarely observed or completely unknown. These challenges are particularly important for in-situ quality control, where defects must be detected or correctly classified for real-time decision-making, including newly emerging defects with limited or unavailable labels. Moreover, for latent defects that cannot be directly inspected online, defects must instead be predicted from indirect process-sensing signals. This requires mapping process-signal changes to possible defects despite scarce or unavailable defect training samples. This talk explores how advances in AI can address these challenges and enable more adaptive and intelligent in-situ quality control and decision-making for smart manufacturing.\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EBio: \u003C\/strong\u003EDr. Judy Jin is the A. Galip Ulsoy Collegiate Professor of Engineering and Professor of Industrial and Operations Engineering at the University of Michigan. Her research lies at the intersection of data science and quality engineering, with a focus on synergistically integrating engineering models, AI, and advanced quality control methods to improve system design and operational performance. She has served as PI\/Co-PI on more than $20 million in federally and industry-funded research. Her work has received numerous honors, including 18 Best Paper Awards, the S.M. Wu Research Implementation Award from SME, the Forging Achievement Award from FIERF, the NSF CAREER Award, and the NSF PECASE Award.\u003Cbr\u003E\u003Cbr\u003EDr. Jin currently serves as Editor-in-Chief of IISE Transactions. She has also served as Vice President of INFORMS, Chair of the INFORMS Quality, Statistics and Reliability Section, and President of the IISE Quality Control and Reliability Engineering Division. She is a Fellow of ASME, IISE, and INFORMS.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAI-Enabled In-Situ Quality Control: Learning Beyond the Known\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"AI-Enabled In-Situ Quality Control: Learning Beyond the Known "}],"uid":"36870","created_gmt":"2026-09-09 18:51:49","changed_gmt":"2026-09-09 22:59:55","author":"bjones434","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-11-20T11:00:00-05:00","event_time_end":"2026-11-20T12:00:00-05:00","event_time_end_last":"2026-11-20T12:00:00-05:00","gmt_time_start":"2026-11-20 16:00:00","gmt_time_end":"2026-11-20 17:00:00","gmt_time_end_last":"2026-11-20 17:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 1502","extras":[],"hg_media":{"681112":{"id":"681112","type":"image","title":"jin-13761.jpg","body":"\u003Cp\u003EJudy Jin\u003C\/p\u003E","created":"1788994226","gmt_created":"2026-09-09 22:50:26","changed":"1788994226","gmt_changed":"2026-09-09 22:50:26","alt":"Judy Jin","file":{"fid":"265471","name":"jin-13761.jpg","image_path":"\/sites\/default\/files\/2026\/09\/09\/jin-13761.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/09\/jin-13761.jpg","mime":"image\/jpeg","size":142752,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/09\/jin-13761.jpg?itok=ofviw9nh"}}},"media_ids":["681112"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"692380":{"#nid":"692380","#data":{"type":"event","title":"Georgia Statistics Day 2026","body":[{"value":"\u003Ch2\u003EGathering Minds Across Georgia: Promoting Interdisciplinary Statistics Research\u003C\/h2\u003E\u003Cp\u003EThe H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology is pleased to welcome you to Atlanta, Georgia for Georgia Statistics Day 2026.\u003C\/p\u003E\u003Cp\u003EGeorgia Statistics Day is an annual event that promotes interdisciplinary statistics research across the University of Georgia, the Georgia Institute of Technology, and Emory University, with the venue rotating among the participating institutions. The 2026 event will feature a keynote lecture, two semi-plenary lectures, parallel research sessions, a student poster session, and ample opportunity for exchange between academia and industry.\u003C\/p\u003E\u003Cp\u003EWe are honored to have Prof. Jianqing Fan, Frederick L. Moore \u201918 Professor of Finance and Professor of Statistics, Machine Learning, and Operations Research and Financial Engineering at Princeton University, as our keynote speaker. The semi-plenary speakers are Prof. Sivaraman Balakrishnan from Carnegie Mellon University and Prof. Mladen Kolar from the University of Southern California.\u003C\/p\u003E\u003Cp\u003EThis one-day workshop brings together faculty, students, and industry researchers from across Georgia and the Southeast for invited talks, interdisciplinary exchange, mentoring, and networking. Registration and poster submissions are open through September 28, 2026.\u003Cbr\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Ca href=\u0022https:\/\/sites.gatech.edu\/gsd2026\/\u0022\u003EGeorgia Statistics Day 2026 website\u003C\/a\u003E\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EGeorgia Statistics Day 2026\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Georgia Statistics Day 2026"}],"uid":"27764","created_gmt":"2026-09-08 14:40:49","changed_gmt":"2026-09-08 14:56:19","author":"Scott Jacobson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-05T08:00:00-04:00","event_time_end":"2026-10-05T17:30:00-04:00","event_time_end_last":"2026-10-05T17:30:00-04:00","gmt_time_start":"2026-10-05 12:00:00","gmt_time_end":"2026-10-05 21:30:00","gmt_time_end_last":"2026-10-05 21:30:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower, Georgia Tech","extras":[],"related_links":[{"url":"https:\/\/sites.gatech.edu\/gsd2026\/","title":"Georgia Statistics Day 2026 website"}],"groups":[{"id":"660346","name":"Master of Science in Analytics"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"194682","name":"Workshop"},{"id":"1789","name":"Conference\/Symposium"},{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022https:\/\/www.isye.gatech.edu\/user\/908\/contact\u0022\u003EMonike Welch\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"692060":{"#nid":"692060","#data":{"type":"event","title":"ISyE Seminar - Weihua An","body":[{"value":"\u003Ch2\u003ETitle:\u0026nbsp;\u003C\/h2\u003E\u003Cp\u003EBayesian Pooling of Self- and Peer-Reports to Improve Measurement of Sensitive Behaviors\u003C\/p\u003E\u003Ch2\u003E\u003Cbr\u003EAbstract:\u0026nbsp;\u003C\/h2\u003E\u003Cp\u003EPrior literature shows that self-reports, especially those of sensitive behaviors, tend to be biased. For example, respondents may over-report their family origin and volunteering experiences while under-reporting their drinking and smoking behaviors. In this study I examine a social network-based approach to addressing self-reporting bias, which is to ask peers (e.g. classmates or co-workers) to provide alternative reports that can be used to cross-validate and supplement self-reports. I first formalize the data generation process statistically by proposing a model containing two sub-models, one for the self-reports and the other for the peer-reports. In each of the sub-models, I treat the observed report as a probabilistic realization of a truthful report and a false report. The model can incorporate both self- and peer-characteristics and also dyadic characteristics. A Bayesian approach helps make the model self-containing by imposing a prior on the unknown ego\u0027s behavior. Then the Bayesian approach simulates self- and peer-reports according to the data generation process iteratively until the simulated reports emulate the observed reports. Through a case study on self- and peer-reports of smoking among adolescents, I demonstrate that the Bayesian approach can not only reveal how multiple characteristics are related to reporting biases but also incorporate these characteristics effectively into the imputation of the true behavior.\u003C\/p\u003E\u003Cp\u003EKeywords: Self-reporting Bias; Peer Reports; Multiple Reports; Informant Accuracy\u003C\/p\u003E\u003Ch2\u003EBio:\u0026nbsp;\u003C\/h2\u003E\u003Cp\u003EDr. Weihua An is Professor and Chair of Sociology and Professor of Data and Decision Sciences at Emory University. He is also an affiliated faculty member of the East Asian Studies Program, the Goizueta Business School, and the Rollins School of Public Health. He earned his Ph.D. in Sociology and A.M. in Statistics from Harvard University. Dr. An\u0027s research advances theories and methods in network analysis and causal inference. He has published widely in both methodological and substantive journals and also authored multiple statistical packages, which have received 200K downloads in total. He currently serves as the Editor of Sociological Methodology and the Chair-Elect of the Methodology section of the American Sociological Association. He is a recipient of the Faculty Teaching Award from Emory Sociology and the Clifford Clogg Award and the Leo Goodman Award from the American Sociological Association. He has advised 28 PhD dissertations and ten undergraduate honors theses.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EPrior literature shows that self-reports, especially those of sensitive behaviors, tend to be biased. For example, respondents may over-report their family origin and volunteering experiences while under-reporting their drinking and smoking behaviors. In this study I examine a social network-based approach to addressing self-reporting bias, which is to ask peers (e.g. classmates or co-workers) to provide alternative reports that can be used to cross-validate and supplement self-reports. I first formalize the data generation process statistically by proposing a model containing two sub-models, one for the self-reports and the other for the peer-reports. In each of the sub-models, I treat the observed report as a probabilistic realization of a truthful report and a false report. The model can incorporate both self- and peer-characteristics and also dyadic characteristics. A Bayesian approach helps make the model self-containing by imposing a prior on the unknown ego\u2019s behavior. Then the Bayesian approach simulates self- and peer-reports according to the data generation process iteratively until the simulated reports emulate the observed reports. Through a case study on self- and peer-reports of smoking among adolescents, I demonstrate that the Bayesian approach can not only reveal how multiple characteristics are related to reporting biases but also incorporate these characteristics effectively into the imputation of the true behavior.\u003C\/p\u003E\u003Cp\u003EKeywords: Self-reporting Bias; Peer Reports; Multiple Reports; Informant Accuracy\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Bayesian Pooling of Self- and Peer-Reports to Improve Measurement of Sensitive Behaviors"}],"uid":"36870","created_gmt":"2026-08-27 14:46:38","changed_gmt":"2026-08-31 13:50:49","author":"bjones434","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-04T11:00:00-04:00","event_time_end":"2026-09-04T12:00:00-04:00","event_time_end_last":"2026-09-04T12:00:00-04:00","gmt_time_start":"2026-09-04 15:00:00","gmt_time_end":"2026-09-04 16:00:00","gmt_time_end_last":"2026-09-04 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 15th Floor. Room 1502","extras":[],"hg_media":{"681007":{"id":"681007","type":"image","title":"Weihua An","body":null,"created":"1788184023","gmt_created":"2026-08-31 13:47:03","changed":"1788184023","gmt_changed":"2026-08-31 13:47:03","alt":"Weihua An","file":{"fid":"265354","name":"Weihua_An.jpg","image_path":"\/sites\/default\/files\/2026\/08\/31\/Weihua_An.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/08\/31\/Weihua_An.jpg","mime":"image\/jpeg","size":43016,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/08\/31\/Weihua_An.jpg?itok=Fhky3Z5Y"}}},"media_ids":["681007"],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"691914":{"#nid":"691914","#data":{"type":"event","title":"Welcome to George Tower Challenge","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003EHow It Works\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003E\u2022 Complete the five challenges below.\u003Cbr\u003E\u2022 Each challenge is worth 10 points.\u003Cbr\u003E\u2022 Complete all five on September 3rd \u0026nbsp;for a 10-point bonus.\u003Cbr\u003E\u2022 40 points = Ice Cream Ticket\u003Cbr\u003E\u2022 50 points = ISyE Swag Giveaway Drawing Entry Ticket\u003Cbr\u003E\u2022 60 points = Grand Prize Drawing Entry Ticket\u003C\/p\u003E\u003Cp\u003E\u003Cem\u003E\u003Cstrong\u003E**Please note that Challenges 2, 3, and 4 will be available only on Thursday, September 3, 11am-12:15pm only.\u003C\/strong\u003E\u003C\/em\u003E\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EChallenge 1:\u0026nbsp; Photo Quest (Worth: 10 Points)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ECapture George Tower, study spaces\/Collaborative Learning Space(s), student organizations, faculty member, at least three new ISyE students, CASE team member(s), Academic Office team member(s), XR Makerspace, and what you would consider the best view from the building.\u0026nbsp; Upload and tag gt_isye on Instagram to receive points for this challenge. See attached flyer for more information on how to upload.\u0026nbsp;\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EChallenge 2:\u0026nbsp; Club Crawl (Worth: 10 Points)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EVisit Alpha Phi Mu, BISyE, IISE, Student Ambassadors, Supply Chain\u0026amp; Logistics Club, and WISyE.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003E\u0026nbsp;Challenge 3:\u0026nbsp; Resource Rally (Worth: 10 Points)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EVisit Academics (Advising, OR Master\u2019s in IE, OR MSA, OR, PhD tables), CASE, ISyE XR Makerspace, and Faculty Undergraduate Research labs.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EChallenge 4:\u0026nbsp; Did You Know? Discovery (Worth: 10 Points)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ECollect fun facts from offices, labs, and organizations that you visit. You can continue to visit the Academic Office (houses Advising, Master\u2019s and PhD in IE, MSA, and CASE) after the \u201ckickoff\u201d to find your \u201cfun fact\u201d throughout the week.\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EChallenge 5:\u0026nbsp; Leave Your Mark (Worth: 10 Points)\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003EComplete the \u003Cstrong\u003EAchievement Board\u003C\/strong\u003E \u003Cstrong\u003EAND\u003C\/strong\u003E answer a prompt on the \u003Cstrong\u003EISyE Wall\u003C\/strong\u003E.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003E\u003Cstrong\u003EComplete challenges, earn points, and win prizes!\u003C\/strong\u003E\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Explore \u2022 Connect \u2022 Discover"}],"uid":"36760","created_gmt":"2026-08-24 17:24:47","changed_gmt":"2026-08-26 14:31:04","author":"jsmith830","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-09-03T00:00:00-04:00","event_time_end":"2026-09-11T23:59:59-04:00","event_time_end_last":"2026-09-11T23:59:59-04:00","gmt_time_start":"2026-09-03 04:00:00","gmt_time_end":"2026-09-12 03:59:59","gmt_time_end_last":"2026-09-12 03:59:59","rrule":null,"timezone":"America\/New_York"},"location":"George Tower","extras":[],"hg_media":{"680963":{"id":"680963","type":"image","title":"George Tower Photo Challenge","body":"\u003Cp\u003EGeorge Tower Photo Challenge\u003C\/p\u003E","created":"1787592547","gmt_created":"2026-08-24 17:29:07","changed":"1787592547","gmt_changed":"2026-08-24 17:29:07","alt":"George Tower Photo Challenge","file":{"fid":"265303","name":"4.png","image_path":"\/sites\/default\/files\/2026\/08\/24\/4.png","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/08\/24\/4.png","mime":"image\/png","size":1032308,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/08\/24\/4.png?itok=Yj6-Vla-"}}},"media_ids":["680963"],"groups":[{"id":"1250","name":"Center for Health and Humanitarian Systems (CHHS)"},{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"691878":{"#nid":"691878","#data":{"type":"event","title":"ISyE Seminar - Getachew-Biru Worku ","body":[{"value":"\u003Cp\u003ETitle:\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EDesign and Techno-Economic Analysis of PV Powered Irrigation System: Case Study in\u003Cbr\u003ERwanda\u003C\/p\u003E\u003Cp\u003E\u003Cbr\u003EAbstract:\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EThe agriculture sector is a major economic driver for Africa. However, climatic change is driving severe disruption across Africa, causing prolonged dry seasons and erratic rainfall. As a result, farmers are facing lower farming yield. To mitigate this serious challenge, farmers must adopt modern and green technologies, like solar irrigation. To show the potential of solar irrigation system to mitigate this critical problem, a research project has been developed with the collaboration of Georgia Tech, University of Rwanda and Adama Science and Technology University. The project aims at developing a PV irrigation system that integrates IoT and controllers for real-time monitoring of the performance of the PV-irrigation system and for optimizing water conservation. This project is envisioned to be a prototype model for further scaling up the deployment of PV-irrigation systems in Africa to enhance sustainable agricultural.\u0026nbsp;\u003Cbr\u003EAs part of the whole project, this seminar focuses more on the design and economic assessment of the system for a particular village in Rwanda.\u003C\/p\u003E\u003Cp\u003E\u003Cbr\u003EBio:\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EGetachew Biru Worku obtained his MSC and PhD in Electrical Engineering from Dresden University of\u0026nbsp;\u003Cbr\u003ETechnology, Germany. He has more than 30 years of academic and research experience in academic institutions and industry. He has extensive experience in teaching a broad range of electrical engineering courses with excellent feedback and acknowledgements from faculties and students. He has been lecturing courses such as Power Quality and Reliability, Power System Operation and Control, High Voltage Engineering, Power System Analysis, Power Transmission and Distribution Engineering, Electrical Machines Design, Smart Grid and Traction Power System in various Ethiopian Universities and University of Rwanda. He is currently employed as an associate professor at the University of Rwanda giving lectures and advising postgraduate students. He is a dedicated researcher in renewable energy deployment focusing on reliability of off-grid and microgrids to bring sustainable electrical power to the underserved areas. His research areas are electrical power and renewable energy and has authored and co-authored more than 45 papers in peer-reviewed journals.\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe agriculture sector is a major economic driver for Africa. However, climatic change is driving severe disruption across Africa, causing prolonged dry seasons and erratic rainfall. As a result, farmers are facing lower farming yield. To mitigate this serious challenge, farmers must adopt modern and green technologies, like solar irrigation. To show the potential of solar irrigation system to mitigate this critical problem, a research project has been developed with the collaboration of Georgia Tech, University of Rwanda and Adama Science and Technology University. The project aims at developing a PV irrigation system that integrates IoT and controllers for real-time monitoring of the performance of the PV-irrigation system and for optimizing water conservation. This project is envisioned to be a prototype model for further scaling up the deployment of PV-irrigation systems in Africa to enhance sustainable agricultural. As part of the whole project, this seminar focuses more on the design and economic assessment of\u0026nbsp;\u003Cbr\u003Ethe system for a particular village in Rwanda.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Design and Techno-Economic Analysis of PV Powered Irrigation System: Case Study in Rwanda"}],"uid":"36870","created_gmt":"2026-08-21 19:16:14","changed_gmt":"2026-08-21 19:16:14","author":"bjones434","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-08-28T11:00:00-04:00","event_time_end":"2026-08-28T12:00:00-04:00","event_time_end_last":"2026-08-28T12:00:00-04:00","gmt_time_start":"2026-08-28 15:00:00","gmt_time_end":"2026-08-28 16:00:00","gmt_time_end_last":"2026-08-28 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"George Tower 15th Floor. Room 1502","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1795","name":"Seminar\/Lecture\/Colloquium"}],"invited_audience":[{"id":"194945","name":"Alumni"},{"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":[],"email":[],"slides":[],"orientation":[],"userdata":""}},"683184":{"#nid":"683184","#data":{"type":"event","title":"(CANCELED) SCL Course: Engineering the Warehouse (Virtual\/Instructor-led)","body":[{"value":"\u003Ch4\u003ECOURSE DESCRIPTION\u003C\/h4\u003E\u003Cp\u003EThe requirement for high levels of customer service, increasing numbers of SKUs and high labor costs have dramatically increased the complexity of warehouse operations. It is no longer sufficient to manage a warehouse based on a simple, arbitrary \u201cABC\u201d classification of SKUs, which treats all those in a category as if they were identical. Instead, each decision \u2013 such as where to store or where to pick product \u2013 must be based on careful engineering and economic analysis. Each SKU must identify its own cheapest, fastest path through the warehouse to the customer and then compete with all the other SKUs for the necessary resources. This results in warehouse operations that are finely tuned to patterns of customer orders and maximally efficient. Learn the concepts necessary to address modern warehouse trade-offs between space and time in optimizing and managing your warehouse.\u003C\/p\u003E\u003Cp\u003EEssential learning for those who are seeking cost reductions through better handling methods. Also valuable for those who must replace, upgrade, or add material handling equipment.\u0026nbsp;The two-day course will include case examples and a guided exercise to ensure mastery of the techniques presented.\u003C\/p\u003E\u003Ch4\u003EWHO SHOULD ATTEND\u003C\/h4\u003E\u003Cp\u003ESupply chain and logistics consultants, supply chain engineers and analysts, facility engineers, and warehouse supervisors and team leaders\u003C\/p\u003E\u003Ch4\u003EHOW YOU WILL BENEFIT\u003C\/h4\u003E\u003Cp\u003E\u003Cstrong\u003EUpon completion of this course, you will be able to:\u003C\/strong\u003E\u003C\/p\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e918aa38aebac7aacbf2d504b380c0876\u0022\u003EExchange space for time (or vice versa) to better meet business objectives.\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e2bfd28dbbbe907d0601a63c64b1d17b2\u0022\u003EUnderstand when to use dedicated storage and when to use shared storage.\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e5354bd5f9f723243a7f7e9108501965b\u0022\u003EIdentify the most convenient locations in a warehouse based on an economic model.\u003C\/li\u003E\u003Cli data-list-item-id=\u0022eed01e785b2a77d1b689343f96f5880cf\u0022\u003EIdentify patterns in customer orders and exploit these to speed fulfillment.\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e031f35b5321ca70cd9503554a407fd24\u0022\u003EEvaluate warehouse performance.\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e8935c51e97543ba468f4c8fd8df2cac4\u0022\u003EOptimally size and stock a forward pick area.\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e0bdbf197eaa24d64773f6e79c01d15be\u0022\u003EUnderstand the best practices in order-picking.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch4\u003EWHAT IS COVERED\u003C\/h4\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022ee977921b1d5c4838d7b2ae47cb4dfdf5\u0022\u003EWarehouse performance\u003C\/li\u003E\u003Cli data-list-item-id=\u0022eac19b859ba071446f8baa0709fdd5aeb\u0022\u003EModern warehouse trade-offs\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e41db827b1d324236944aba50fdeff676\u0022\u003ESize and stocking optimization\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e26310b215ecab6551f0a4af27caf1c7b\u0022\u003EOrder-picking best practices\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e7fcb4c110b6b4a4768baf1d068b44cb9\u0022\u003EAutomation\u003C\/li\u003E\u003C\/ul\u003E\u003Ch4\u003ECOURSE MATERIALS\u003C\/h4\u003E\u003Cul\u003E\u003Cli data-list-item-id=\u0022e0643cd5360639ab97b46c5a02117bdd3\u0022\u003EOnline access to course material in electronic format\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e1f133485943e38a66c542fe6bb346e2f\u0022\u003EAccess to an e-copy of the book \u201cWarehouse \u0026amp; Distribution Science\u201d\u0026nbsp;as well as access to an accompanying suite of software to aid in warehouse analytics and optimization.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch4\u003ECOURSE PREREQUISITES\u003C\/h4\u003E\u003Cp\u003ENone.\u003C\/p\u003E\u003Ch4\u003ECERTIFICATE INFORMATION\u003C\/h4\u003E\u003Cp\u003EThis course is part of the \u003Ca href=\u0022https:\/\/www.scl.gatech.edu\/education\/professional-education\/courses#DOAD\u0022\u003EDistribution Operations Analysis \u0026amp; Design (DOAD) Certificate\u003C\/a\u003E.\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe requirement for high levels of customer service, increasing numbers of SKUs and high labor costs have dramatically increased the complexity of warehouse operations. It is no longer sufficient to manage a warehouse based on a simple, arbitrary \u201cABC\u201d classification of SKUs, which treats all those in a category as if they were identical. Instead, each decision \u2013 such as where to store or where to pick product \u2013 must be based on careful engineering and economic analysis.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn the concepts necessary to address modern warehouse trade-offs between space and time in optimizing and managing your warehouse."}],"uid":"27233","created_gmt":"2025-07-18 19:23:59","changed_gmt":"2026-07-21 13:32:18","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-08-10T08:00:00-04:00","event_time_end":"2026-08-12T17:00:00-04:00","event_time_end_last":"2026-08-12T17:00:00-04:00","gmt_time_start":"2026-08-10 12:00:00","gmt_time_end":"2026-08-12 21:00:00","gmt_time_end_last":"2026-08-12 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Online\/Virtually-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/engwh","title":"Course webpage within the SCL website"}],"groups":[{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"6140","name":"warehousing"},{"id":"7149","name":"inventory"},{"id":"167167","name":"storage"},{"id":"122741","name":"physical internet"},{"id":"143871","name":"Physical Internet Center"},{"id":"186857","name":"go-gtmi"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"10377","name":"Career\/Professional development"}],"invited_audience":[{"id":"78771","name":"Public"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[{"value":"\u003Cp\u003E\u003Ca href=\u0022mailto:info@scl.gatech.edu\u0022\u003Einfo@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}