{"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":"\u003Cp\u003EThe Sharp Minimax Risk for High-Dimensional Uniformity Testing and Applications to Model Calibration\u003C\/p\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 21:53:00","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":"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":"2026-09-14 17:54:33","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":{"681146":{"id":"681146","type":"image","title":"Omar El Housni","body":null,"created":"1789408448","gmt_created":"2026-09-14 17:54:08","changed":"1789408448","gmt_changed":"2026-09-14 17:54:08","alt":"Omar El Housni","file":{"fid":"265507","name":"el-housni-13725.jpg","image_path":"\/sites\/default\/files\/2026\/09\/14\/el-housni-13725.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/14\/el-housni-13725.jpg","mime":"image\/jpeg","size":75907,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/14\/el-housni-13725.jpg?itok=g7EorVKL"}}},"media_ids":["681146"],"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":"2026-09-14 17:36:36","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":{"681144":{"id":"681144","type":"image","title":"Judy Jin","body":"\u003Cp\u003EJudy Jin\u003C\/p\u003E","created":"1789407369","gmt_created":"2026-09-14 17:36:09","changed":"1789407369","gmt_changed":"2026-09-14 17:36:09","alt":"Judy Jin2","file":{"fid":"265505","name":"Judy-Jin.jpg","image_path":"\/sites\/default\/files\/2026\/09\/14\/Judy-Jin.jpg","image_full_path":"http:\/\/hg.gatech.edu\/\/sites\/default\/files\/2026\/09\/14\/Judy-Jin.jpg","mime":"image\/jpeg","size":81518,"path_740":"http:\/\/hg.gatech.edu\/sites\/default\/files\/styles\/740xx_scale\/public\/2026\/09\/14\/Judy-Jin.jpg?itok=xMCp9Gjo"}}},"media_ids":["681144"],"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":""}},"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":""}},"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. 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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. 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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":""}},"690421":{"#nid":"690421","#data":{"type":"event","title":"SCL Course: Transforming Supply Chain Management and Performance Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course is the first in the four-course Supply Chain Analytics Professional certificate program. It prepares you to apply leading-edge analytical methods and technology enablers across the supply chain. You\u2019ll learn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u2019ll learn about data cleansing, exploratory data analysis, and visualization. You\u2019ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\u003Cp\u003EThe online version of the course is comprised of (4) half-day instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EUnderstand the most relevant planning challenges across the strategic, tactical, and operational levels of supply chains\u003C\/li\u003E\u003Cli\u003ELearn the difference between analytics types, the links between them, and how to best use them to improve\u0026nbsp;supply chain management (SCM)\u0026nbsp;processes\u003C\/li\u003E\u003Cli\u003EUse\u0026nbsp;Key Performance Indicators (KPIs)\u0026nbsp;to find causes of underperformance in supply chains and to plan for analytics projects that will address strategic SCM goals\u003C\/li\u003E\u003Cli\u003EUtilize Python and PowerBI to understand, visualize, and analyze data in order to prepare for deeper analytics\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EThe role of analytics in SCM\u003C\/li\u003E\u003Cli\u003ETypes of analytics (descriptive, diagnostic, predictive, and prescriptive) and the relationships between them\u003C\/li\u003E\u003Cli\u003EPreprocessing (cleaning and integrating) data as it relates to SCM\u003C\/li\u003E\u003Cli\u003EConducting exploratory data analysis on supply chain data\u003C\/li\u003E\u003Cli\u003EBest practices for visualizing data and building dashboards\u003C\/li\u003E\u003Cli\u003EIdentifying and analyzing KPIs of SCM\u003C\/li\u003E\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn the dynamics of supply chains, the most relevant planning challenges, and the roles of different types of analytics. Next, you\u2019ll learn about data cleansing, exploratory data analysis, and visualization. You\u2019ll use Python and PowerBI to analyze the causes of underperformance and to build dashboards to visualize supply chain data. You will leave knowing how to gather, analyze, and prepare your data through descriptive analytics before you dig into deeper applications.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to apply leading-edge analytical methods and technology enablers across the supply chain"}],"uid":"27233","created_gmt":"2026-05-21 17:48:43","changed_gmt":"2026-05-22 19:52:13","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2027-02-22T13:00:00-05:00","event_time_end":"2027-02-25T17:00:00-05:00","event_time_end_last":"2027-02-25T17:00:00-05:00","gmt_time_start":"2027-02-22 18:00:00","gmt_time_end":"2027-02-25 22:00:00","gmt_time_end_last":"2027-02-25 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scapa","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"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":""}},"690426":{"#nid":"690426","#data":{"type":"event","title":"SCL Course: Machine Learning Applications for Supply Chain Planning (Virtual\/Instructor-Lead)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course is the third in the four-course Supply Chain Analytics Professional certificate program. It introduces the field of machine learning, an area where algorithms learn patterns from data to support proactive decision making, as it applies to supply chain management. You\u2019ll use machine learning to conduct predictive analytics as you forecast future demand, develop inventory policies, perform customer segmentation and predictive maintenance. You\u2019ll use Python and PowerBI to create and analyze regression, clustering, and classification models.\u003C\/p\u003E\u003Cp\u003EThe course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed\u0026nbsp;before the first day of the course. An optional pre-course webinar is typically held the Thursday\u0026nbsp;before the course start date (July 6).\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EUnderstand the role of machine learning (ML) in Supply Chain Management (SCM)\u003C\/li\u003E\u003Cli\u003EApply advanced analytics techniques to build planning tools that can leverage large and real-time data sets\u003C\/li\u003E\u003Cli\u003EApply ML in demand forecasting and predictive maintenance\u003C\/li\u003E\u003Cli\u003EUnderstand how to assess ML model performance, improve models, and pick the best model for a decision\u003C\/li\u003E\u003Cli\u003EUse Python and PowerBI to build, analyze, and deploy ML models\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat You Will Learn\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EHow ML relates to SCM\u003C\/li\u003E\u003Cli\u003EML algorithms such as regression trees, clustering techniques, decision trees, random forests, logistic regression\u003C\/li\u003E\u003Cli\u003EAspects of ML projects including parameter tuning, cross validation, and assess model performance\u003C\/li\u003E\u003Cli\u003EApplication of ML in demand forecasting for sales and operations planning (S\u0026amp;OP) and inventory management\u003C\/li\u003E\u003Cli\u003EApplication of ML in predictive maintenance\u003C\/li\u003E\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EThe course will cover regression (trees), advanced time series forecasting, various clustering techniques (such as k-means), decision trees, random forests, neural nets, logistic regression, and Bayes classifiers. Using Power BI and Python, you\u2019ll apply the techniques to sensor data of the fictional Cardboard Company\u2019s paper production to build an anomaly detection model that supports proactive production maintenance planning.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Apply machine learning with Python and Power BI to optimize supply chain forecasting, inventory, and maintenance."}],"uid":"27233","created_gmt":"2026-05-21 18:07:55","changed_gmt":"2026-05-21 18:09:24","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2027-09-13T13:00:00-04:00","event_time_end":"2027-09-16T17:00:00-04:00","event_time_end_last":"2027-09-16T17:00:00-04:00","gmt_time_start":"2027-09-13 17:00:00","gmt_time_end":"2027-09-16 21:00:00","gmt_time_end_last":"2027-09-16 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaml","title":"Course webpage within the SCL website"}],"groups":[{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"170001","name":"Supply Chain Engineering"},{"id":"194222","name":"Supply chain "},{"id":"9167","name":"machine learning"},{"id":"122741","name":"physical internet"}],"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\u003Einfo@scl.gatech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"690425":{"#nid":"690425","#data":{"type":"event","title":"SCL Course: Generative AI Application for Supply Chain Professionals (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course provides a deep dive into the ways in which artificial intelligence (AI) optimizes supply chain efficiency. Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization. The course also covers ethical AI use, good and bad use of generative AI (GenAI), and rapidly emerging use cases. By the end, professionals will be skilled in applying AI to enhance supply chain processes and drive success in their organizations.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course targets supply chain managers, data analysts, logistics professionals, procurement specialists, and business leaders aiming to harness GenAI for enhanced supply chain operations. It is ideal for those interested in GenAI-driven efficiency, strategic insights, and navigation of GenAI\u0027s role in transforming supply chain processes.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EEnhance decision-making capabilities through GenAI-driven insights to optimize processes and boost efficiency.\u003C\/li\u003E\u003Cli\u003EAcquire practical skills in prompt engineering and the use of generative AI models.\u003C\/li\u003E\u003Cli\u003EExplore practical use cases that can be reapplied.\u003C\/li\u003E\u003Cli\u003ELearn about good and bad use of GenAI for individuals, teams, and organizations.\u003C\/li\u003E\u003Cli\u003EBecome better equipped to effectively harness GenAI capabilities in supply chain activities and planning.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EFoundational understanding of using GenAI in supply chain management\u003C\/li\u003E\u003Cli\u003EBasics of GenAI\u003C\/li\u003E\u003Cli\u003ECrafting effective AI prompts and their applications in optimizing warehouse layouts\u003C\/li\u003E\u003Cli\u003EPredictive maintenance and supplier selection\u003C\/li\u003E\u003Cli\u003EElimination of redundant tasks through AI\u003C\/li\u003E\u003Cli\u003EEthical considerations, risk assessments, and strategy for AI adoption\u003C\/li\u003E\u003Cli\u003EPractical strategies and real-world examples for implementing AI solutions effectively and making informed decisions\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EParticipants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization."}],"uid":"27233","created_gmt":"2026-05-21 18:04:18","changed_gmt":"2026-05-21 18:05:06","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2027-04-19T20:00:00-04:00","event_time_end":"2027-04-21T16:00:00-04:00","event_time_end_last":"2027-04-21T16:00:00-04:00","gmt_time_start":"2027-04-20 00:00:00","gmt_time_end":"2027-04-21 20:00:00","gmt_time_end_last":"2027-04-21 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/gaiascp","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"192390","name":"generative AI"},{"id":"170001","name":"Supply Chain Engineering"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"},{"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:course@scl.gatech.edu\u0022\u003Ecourse@scl.gatech.edu\u003C\/a\u003E\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}},"690424":{"#nid":"690424","#data":{"type":"event","title":"SCL Course: Generative AI Application for Supply Chain Professionals (Onsite\/In-Person)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course provides a deep dive into the ways in which artificial intelligence (AI) optimizes supply chain efficiency. Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization. The course also covers ethical AI use, good and bad use of generative AI (GenAI), and rapidly emerging use cases. By the end, professionals will be skilled in applying AI to enhance supply chain processes and drive success in their organizations.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course targets supply chain managers, data analysts, logistics professionals, procurement specialists, and business leaders aiming to harness GenAI for enhanced supply chain operations. It is ideal for those interested in GenAI-driven efficiency, strategic insights, and navigation of GenAI\u0027s role in transforming supply chain processes.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EEnhance decision-making capabilities through GenAI-driven insights to optimize processes and boost efficiency.\u003C\/li\u003E\u003Cli\u003EAcquire practical skills in prompt engineering and the use of generative AI models.\u003C\/li\u003E\u003Cli\u003EExplore practical use cases that can be reapplied.\u003C\/li\u003E\u003Cli\u003ELearn about good and bad use of GenAI for individuals, teams, and organizations.\u003C\/li\u003E\u003Cli\u003EBecome better equipped to effectively harness GenAI capabilities in supply chain activities and planning.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EFoundational understanding of using GenAI in supply chain management\u003C\/li\u003E\u003Cli\u003EBasics of GenAI\u003C\/li\u003E\u003Cli\u003ECrafting effective AI prompts and their applications in optimizing warehouse layouts\u003C\/li\u003E\u003Cli\u003EPredictive maintenance and supplier selection\u003C\/li\u003E\u003Cli\u003EElimination of redundant tasks through AI\u003C\/li\u003E\u003Cli\u003EEthical considerations, risk assessments, and strategy for AI adoption\u003C\/li\u003E\u003Cli\u003EPractical strategies and real-world examples for implementing AI solutions effectively and making informed decisions\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EParticipants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization."}],"uid":"27233","created_gmt":"2026-05-21 18:02:33","changed_gmt":"2026-05-21 18:03:18","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2027-10-18T20:00:00-04:00","event_time_end":"2027-10-20T16:00:00-04:00","event_time_end_last":"2027-10-20T16:00:00-04:00","gmt_time_start":"2027-10-19 00:00:00","gmt_time_end":"2027-10-20 20:00:00","gmt_time_end_last":"2027-10-20 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Georgia Tech Savannah","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/gaiascp","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"192390","name":"generative AI"},{"id":"170001","name":"Supply Chain Engineering"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"},{"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":""}},"690423":{"#nid":"690423","#data":{"type":"event","title":"SCL Course: Supply Chain Optimization and Prescriptive Analytics (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You\u2019ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you\u2019ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EUse mathematical optimization to transform Supply Chain Management (SCM) processes.\u003C\/li\u003E\u003Cli\u003EApply LP, MIP, and heuristics to SCM, particularly in production planning, routing, and network design.\u003C\/li\u003E\u003Cli\u003EUtilize PowerBI and Python in optimization projects.\u003C\/li\u003E\u003Cli\u003EParticipate in a hackathon that pulls together everything learned throughout the certificate program.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003ERole of mathematical optimization in addressing complex SCM challenges \u0026nbsp;\u003C\/li\u003E\u003Cli\u003EAppropriate application of linear programming (LP), mixed integer programming (MIP), and heuristics\u003C\/li\u003E\u003Cli\u003EEvaluation of production processes, distribution networks, and routes using optimization\u003C\/li\u003E\u003Cli\u003EAbility to pull together all content of the certificate program into a prescriptive analytics project\u003C\/li\u003E\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn advanced analytics and mathematical optimization to find solutions for supply chain problems.\u0026nbsp;The course also serves as a capstone for the Supply Chain Analytics Professional certificate program\u0026nbsp;by culminating in a hackathon where you\u2019ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn advanced analytics and mathematical optimization to find solutions for supply chain problems."}],"uid":"27233","created_gmt":"2026-05-21 17:51:08","changed_gmt":"2026-05-21 17:52:02","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2027-11-08T13:00:00-05:00","event_time_end":"2027-11-11T17:00:00-05:00","event_time_end_last":"2027-11-11T17:00:00-05:00","gmt_time_start":"2027-11-08 18:00:00","gmt_time_end":"2027-11-11 22:00:00","gmt_time_end_last":"2027-11-11 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaoc","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"},{"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":""}},"690422":{"#nid":"690422","#data":{"type":"event","title":"SCL Course: Creating Business Value with Statistical Analysis (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course is the second in the four-course Supply Chain Analytics Professional certificate program. It emphasizes operational performance metrics to align supply chain management with strategic business goals. You\u2019ll learn several statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) along with inventory management models. You\u2019ll use diagnostic analytics with PowerBI and Python to conduct demand and service profiling, undertake root cause analysis, and use time series forecasting in inventory management.\u003C\/p\u003E\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EUnderstand why and how to align Supply Chain Management (SCM) strategy with business strategy\u003C\/li\u003E\u003Cli\u003ELearn statistics techniques as they relate to SCM\u003C\/li\u003E\u003Cli\u003EUnderstand inventory management models and how to apply statistics techniques to them\u003C\/li\u003E\u003Cli\u003ECreate time series forecasts based on SCM data\u003C\/li\u003E\u003Cli\u003EUtilize Python and PowerBI to perform statistical analyses, create time series forecasts and visualize results\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EThe importance of aligning SCM and business strategy\u003C\/li\u003E\u003Cli\u003EHow to ask the right business questions as they relate to SCM\u003C\/li\u003E\u003Cli\u003EHow to use statistics to identify issues, compare data, and forecast decision outcomes\u003C\/li\u003E\u003Cli\u003EStatistical\u0026nbsp;concepts including variance analysis and hypothesis testing\u003C\/li\u003E\u003Cli\u003EInventory management models\u003C\/li\u003E\u003Cli\u003EApplying statistics to inventory management models\u003C\/li\u003E\u003Cli\u003EForecasting techniques including time series forecasting\u003C\/li\u003E\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models to improve operational performance metrics and align supply chain management with strategic business goals.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn statistics concepts (e.g. variance analysis, hypothesis testing, forecasting methods) and inventory management models."}],"uid":"27233","created_gmt":"2026-05-21 17:50:11","changed_gmt":"2026-05-21 17:50:49","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2027-04-12T13:00:00-04:00","event_time_end":"2027-04-15T17:00:00-04:00","event_time_end_last":"2027-04-15T17:00:00-04:00","gmt_time_start":"2027-04-12 17:00:00","gmt_time_end":"2027-04-15 21:00:00","gmt_time_end_last":"2027-04-15 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scabv","title":"Course detail within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"}],"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":""}},"686798":{"#nid":"686798","#data":{"type":"event","title":"SCL Course: Generative AI Application for Supply Chain Professionals (Onsite\/In-Person)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course provides a deep dive into the ways in which artificial intelligence (AI) optimizes supply chain efficiency. Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization. The course also covers ethical AI use, good and bad use of generative AI (GenAI), and rapidly emerging use cases. By the end, professionals will be skilled in applying AI to enhance supply chain processes and drive success in their organizations.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course targets supply chain managers, data analysts, logistics professionals, procurement specialists, and business leaders aiming to harness GenAI for enhanced supply chain operations. It is ideal for those interested in GenAI-driven efficiency, strategic insights, and navigation of GenAI\u0027s role in transforming supply chain processes.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EEnhance decision-making capabilities through GenAI-driven insights to optimize processes and boost efficiency.\u003C\/li\u003E\u003Cli\u003EAcquire practical skills in prompt engineering and the use of generative AI models.\u003C\/li\u003E\u003Cli\u003EExplore practical use cases that can be reapplied.\u003C\/li\u003E\u003Cli\u003ELearn about good and bad use of GenAI for individuals, teams, and organizations.\u003C\/li\u003E\u003Cli\u003EBecome better equipped to effectively harness GenAI capabilities in supply chain activities and planning.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EFoundational understanding of using GenAI in supply chain management\u003C\/li\u003E\u003Cli\u003EBasics of GenAI\u003C\/li\u003E\u003Cli\u003ECrafting effective AI prompts and their applications in optimizing warehouse layouts\u003C\/li\u003E\u003Cli\u003EPredictive maintenance and supplier selection\u003C\/li\u003E\u003Cli\u003EElimination of redundant tasks through AI\u003C\/li\u003E\u003Cli\u003EEthical considerations, risk assessments, and strategy for AI adoption\u003C\/li\u003E\u003Cli\u003EPractical strategies and real-world examples for implementing AI solutions effectively and making informed decisions\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EParticipants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization.\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Participants will explore generative AI fundamentals, prompt engineering, and practical applications such as automated inventory systems, predictive maintenance, and route optimization."}],"uid":"27233","created_gmt":"2025-12-08 22:20:10","changed_gmt":"2025-12-08 22:20:47","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-19T20:00:00-04:00","event_time_end":"2026-10-21T16:00:00-04:00","event_time_end_last":"2026-10-21T16:00:00-04:00","gmt_time_start":"2026-10-20 00:00:00","gmt_time_end":"2026-10-21 20:00:00","gmt_time_end_last":"2026-10-21 20:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Georgia Tech Savannah","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/gaiascp","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"192390","name":"generative AI"},{"id":"170001","name":"Supply Chain Engineering"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"},{"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":""}},"682843":{"#nid":"682843","#data":{"type":"event","title":"SCL Course: Supply Chain Optimization and Prescriptive Analytics (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course is the fourth in the 4-course Supply Chain Analytics Professional certificate program. It incorporates learning advanced analytics and mathematical optimization to find solutions for supply chain problems. You\u2019ll learn how to use linear programming, mixed integer programming, and heuristics to conduct prescriptive analytics related to production processes, distribution networks, and routing. The course serves as a capstone for the program by culminating in a hackathon where you\u2019ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\u003Cp\u003EThe online version of the course is comprised of (4) half-day online instructor-led LIVE group webinars and pre-work (e.g. installing and testing software on your computer, testing connectivity with LMS and meeting software, etc.) to be completed before the first day of the course.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EExperienced business professionals who perform or want to perform analytics to improve their supply chain management processes. They want to tackle strategic goals and to perform leading edge analytics projects that address the full complexity of supply chains.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EUse mathematical optimization to transform Supply Chain Management (SCM) processes.\u003C\/li\u003E\u003Cli\u003EApply LP, MIP, and heuristics to SCM, particularly in production planning, routing, and network design.\u003C\/li\u003E\u003Cli\u003EUtilize PowerBI and Python in optimization projects.\u003C\/li\u003E\u003Cli\u003EParticipate in a hackathon that pulls together everything learned throughout the certificate program.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat Is Covered\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003ERole of mathematical optimization in addressing complex SCM challenges \u0026nbsp;\u003C\/li\u003E\u003Cli\u003EAppropriate application of linear programming (LP), mixed integer programming (MIP), and heuristics\u003C\/li\u003E\u003Cli\u003EEvaluation of production processes, distribution networks, and routes using optimization\u003C\/li\u003E\u003Cli\u003EAbility to pull together all content of the certificate program into a prescriptive analytics project\u003C\/li\u003E\u003Cli\u003EHands-on practice with these skills using data from the (fictional) Cardboard Company (CBC)\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ELearn advanced analytics and mathematical optimization to find solutions for supply chain problems.\u0026nbsp;The course also serves as a capstone for the Supply Chain Analytics Professional certificate program\u0026nbsp;by culminating in a hackathon where you\u2019ll design networks, inventory policies, and scenarios and then evaluate the outcomes via simulations.\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn advanced analytics and mathematical optimization to find solutions for supply chain problems."}],"uid":"27233","created_gmt":"2025-06-23 18:09:54","changed_gmt":"2025-06-23 18:10:44","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-11-02T13:00:00-05:00","event_time_end":"2026-11-05T17:00:00-05:00","event_time_end_last":"2026-11-05T17:00:00-05:00","gmt_time_start":"2026-11-02 18:00:00","gmt_time_end":"2026-11-05 22:00:00","gmt_time_end_last":"2026-11-05 22:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/scaoc","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"7251","name":"analytics"},{"id":"167074","name":"Supply Chain"},{"id":"122741","name":"physical internet"},{"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":""}},"682531":{"#nid":"682531","#data":{"type":"event","title":"SCL Course: World Class Sales and Operations Planning (Virtual\/Instructor-led)","body":[{"value":"\u003Ch3\u003E\u003Cstrong\u003ECourse Description\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course focuses on defining, executing, and improving the sales and operations planning (S\u0026amp;OP) process. Participants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of decision support tools to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EWho Should Attend\u003C\/strong\u003E\u003C\/h3\u003E\u003Cp\u003EThis course is designed for chief operating officers; supply chain, sales, marketing and finance management executives (directors, vice presidents, executive vice presidents); supply chain and logistics managers, consultants, supervisors, planners, and engineers; supply chain education and human resource management personnel, inventory and demand planners, and procurement and sourcing analysts and managers; and manufacturing planners, analysts, and managers.\u003C\/p\u003E\u003Ch3\u003E\u003Cstrong\u003EHow You Will Benefit\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003EUnderstand the need for an S\u0026amp;OP process in a company.\u003C\/li\u003E\u003Cli\u003EApply the principles that are the key to success of an S\u0026amp;OP process.\u003C\/li\u003E\u003C\/ul\u003E\u003Ch3\u003E\u003Cstrong\u003EWhat You Will Learn\u003C\/strong\u003E\u003C\/h3\u003E\u003Cul\u003E\u003Cli\u003ES\u0026amp;OP process and technology\u003C\/li\u003E\u003Cli\u003ES\u0026amp;OP implementation planning and execution\u003C\/li\u003E\u003Cli\u003ES\u0026amp;OP stakeholder and communications planning\u003C\/li\u003E\u003Cli\u003ES\u0026amp;OP business case and best practices\u003C\/li\u003E\u003Cli\u003ES\u0026amp;OP process management\u003C\/li\u003E\u003C\/ul\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EParticipants will be introduced to the appropriate stakeholders of S\u0026amp;OP, the importance of S\u0026amp;OP to corporate performance, S\u0026amp;OP cadence, and the use of decision support tools to bring S\u0026amp;OP to the next level. Business cases will be used to show concrete examples of companies where S\u0026amp;OP is effectively applied.\u003C\/p\u003E\u003Ch3\u003E\u0026nbsp;\u003C\/h3\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Learn to define, execute, and improve the sales and operations planning (S\u0026OP) process, including stakeholder management, cadence, and decision support tools, through real-world case studies."}],"uid":"27233","created_gmt":"2025-05-23 20:32:37","changed_gmt":"2025-05-23 20:36:21","author":"Andy Haleblian","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-10-12T08:00:00-04:00","event_time_end":"2026-10-14T12:00:00-04:00","event_time_end_last":"2026-10-14T12:00:00-04:00","gmt_time_start":"2026-10-12 12:00:00","gmt_time_end":"2026-10-14 16:00:00","gmt_time_end_last":"2026-10-14 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Virtual\/Instructor-led","extras":[],"related_links":[{"url":"https:\/\/www.scl.gatech.edu\/education\/professional-education\/course\/wcsop","title":"Course webpage within the SCL website"}],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"},{"id":"1243","name":"The Supply Chain and Logistics Institute (SCL)"}],"categories":[],"keywords":[{"id":"170001","name":"Supply Chain Engineering"},{"id":"194222","name":"Supply chain "},{"id":"194307","name":"Operations Planning"},{"id":"169561","name":"Sales"}],"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\u003Einfo@scl.gatech.edu\u003C\/p\u003E","format":"limited_html"}],"email":[],"slides":[],"orientation":[],"userdata":""}}}