BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//EURO Practitioners&#039; Forum - ECPv6.15.13.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:EURO Practitioners&#039; Forum
X-ORIGINAL-URL:https://www.euro-online.org/websites/or-in-practice
X-WR-CALDESC:Events for EURO Practitioners&#039; Forum
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:UTC
BEGIN:STANDARD
TZOFFSETFROM:+0000
TZOFFSETTO:+0000
TZNAME:UTC
DTSTART:20250101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=UTC:20260306T100000
DTEND;TZID=UTC:20260306T110000
DTSTAMP:20260414T224745
CREATED:20260305T134821Z
LAST-MODIFIED:20260305T134953Z
UID:2190-1772791200-1772794800@www.euro-online.org
SUMMARY:Trust but verify - testing optimization models in real life
DESCRIPTION:Speaker: Richard Oberdieck\, Banking Circle \n“Unless you magically find yourself endowed with limitless programming support\, sooner or later (most likely sooner) you are likely to need to do some coding.” (Paul Rubin) \nBetween a beautiful model on paper and real world impact lies the big gap of implementation. To bridge this gap confidently\, automated tests are a most important pillars on top of which your code rests. However\, many optimization professionals are not familiar with the ins and outs of automated testing. What makes this even more difficult is that writing tests for optimization models specifically is not trivial. Between licensing issues when one uses commercial solvers to run times being many hours\, it is not easy to find a good approach on how to build these solid pillars.In this talk\, I will share what I have learned about testing optimization models over the past 8 years. We will discuss the anatomy of a good test\, what types of testing exists and how property-based testing combined with ChatGPT and good data structures can provide a robust testing setup for code involving optimization models. \nAbout the speaker: \nSince getting his PhD from Imperial College in 2017\, Richard Oberdieck has spent his career at the intersection between code and optimization. First at Ørsted as a software developer for a cable design tool\, then at Gurobi as a technical account manager helping countless customers getting their optimization projects off the ground. Currently\, he works for a bank called Banking Circle as a data scientist\, where he works on a tool which\, if it breaks\, stops all payments in the bank\, leading to an even higher focus on testing than before.
URL:https://www.euro-online.org/websites/or-in-practice/event/trust-but-verify-testing-optimization-models-in-real-life/
ATTACH;FMTTYPE=image/png:https://www.euro-online.org/websites/or-in-practice/wp-content/uploads/sites/8/2026/03/march-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260410T100000
DTEND;TZID=UTC:20260410T110000
DTSTAMP:20260414T224745
CREATED:20260313T142357Z
LAST-MODIFIED:20260313T142357Z
UID:2196-1775815200-1775818800@www.euro-online.org
SUMMARY:A practical approach to replenishment optimization with extended (R\, s\, Q) policy and probabilistic models
DESCRIPTION:Speakers: Alva Presbitero (Senior Applied Scientist\, Zalando) and Shikhar Dev (Senior Machine Learning Engineer\, Zalando) \nIn the high-stakes world of e-commerce\, inventory management is a constant “Inventory Paradox”: carry too much stock and capital is trapped in liquidation; carry too little and you face the “silent killer” of retail—stock-outs. This webinar demonstrates how the ZEOS Inventory Optimization Tool addresses these challenges by unifying probabilistic demand forecasting with Monte Carlo discrete event simulation to drive optimal replenishment decisions. \nThe session is divided into two specialized deep dives: \nPart 1: Applied Science Deep Dive \nWe explore the research and methodology behind the engine\, focusing on these key technical learnings: \n● Extending classical (R\, s\, Q) policies: How we created recommendations that actually fit the fast-paced e-commerce landscape. \n● Probabilistic Demand Modeling: Why our backtest results suggest that modeling full demand probability distributions is far more effective than single-value forecasts. \n● Cost Profile Optimization: How combining probabilistic forecasting with the distribution of our cost profile (optimizing for the 75th percentile) yielded significantly better results than simply looking at the mean. \nPart 2: Machine Learning Engineering Deep Dive \nWe reveal the technical architecture and tools used to put the system into production at scale: \n● Monte Carlo Simulation at Scale: How we used discrete event simulation to stress-test policies across thousands of “alternate timelines” to find the optimal replenishment timing and quantities. \n● Modern ML Stack: A look at how we transitioned research code to scalable and efficient pipelines using AWS\, SageMaker\, and Databricks\, orchestrated by zFlow. \n● Scaling to Millions: Managing feature engineering\, online feature stores\, and real-time inference for millions of SKUs. \nReferences: \n1. AS: https://www.nature.com/articles/s41598-025-32537-2 \n2. MLE: https://engineering.zalando.com/posts/2025/06/inventory-optimisation-system.html \n  \nAbout the speakers: \nAlva Presbitero\, Senior Applied Scientist\, Zalando \nAlva is a Senior Applied Scientist at Zalando\, focusing on the research and data science that powers the ZEOS replenishment engine. She earned her PhD in Computational Science at the University of Amsterdam\, where her research focused on modeling the human innate immune system. Drawing on an extensive background in applied science\, her earlier work was rooted in complexity science\, agent-based modeling\, and computational immunology. \nToday\, she loves using that foundation in complex\, stochastic systems to build scalable and smart inventory solutions for the world of e-commerce. \nShikhar Dev\, Senior Machine Learning Engineer\, Zalando \nShikhar Dev is a founding member of the data and ML engineering team at ZEOS\, where he established the vision and technical foundations for the department’s ML infrastructure. With over a decade of experience and a Master’s in Computer Science from TU Delft\, Shikhar specializes in bridging the gap between research and production. Beyond his work at ZEOS\, Shikhar contributes to Zalando’s broader ML Engineering strategy while also laying the technical foundations for the next generation of GenAI solutions within the department. \n 
URL:https://www.euro-online.org/websites/or-in-practice/event/a-practical-approach-to-replenishment-optimization-with-extended-r-s-q-policy-and-probabilistic-models/
ATTACH;FMTTYPE=image/png:https://www.euro-online.org/websites/or-in-practice/wp-content/uploads/sites/8/2026/03/2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20260427
DTEND;VALUE=DATE:20260429
DTSTAMP:20260414T224745
CREATED:20250620T063738Z
LAST-MODIFIED:20260305T133917Z
UID:1982-1777248000-1777420799@www.euro-online.org
SUMMARY:EURO Practitioners’ Forum 6th Annual Conference
DESCRIPTION:Unlocking OR for all: from Models to Business Impact\nMonday 27 April – Tuesday 28 April 2026 \nWarsaw University of Technology\, Poland\nConference programme \nThe theme of this year’s conference is the end-to-end process of designing\, developing\, and deploying optimization projects. We will discuss not only models and algorithms\, but how Operations Researchers can engage with end users\, stakeholders and work with other specialists to deliver impact in their work. The core focus of the conference is this intersection of research\, expertise and practical applications and how it affects OR projects in all stages\, from conceptualization to practical use. \nThe conference will explore how to make OR solutions more easily accessible to a wider\, non-expert audience\, and discussions and presentations will help us as practitioners better understand how we can bring our solutions into use. The goal is to increase the impact and usage of OR across industries and application domains. \nMore details can be found at https://www.euro-online.org/websites/or-in-practice/euro-practitioners-forum-6th-annual-conference/ \nImportant dates: \n\n11 January\, 2026: Submission deadline\n31 January\, 2026: Notification of acceptance\n20 February\, 2026: Final version of submissions\n5 March\, 2026: Author registration deadline\n20 March\, 2026: Early bird registration deadline (registration for the conference dinner no longer possible after this date)\n\n\nREGISTRATION\n  \nContact \nFor any inquiries\, please contact the conference organisers on this address: epf2026@pw.edu.pl \n  \nSponsors \n \n  \n \n  \n  \n\nKeynote speakers\n\n\nSylwester Ciodyk (Ortec Poland): Practical Optimization: Real-World Success Stories\nPaweł Lichocki (Google): An engineering perspective on mixed integer programming in computer systems\nMichał Kłos (PSE S.A. (the Polish Transmission System Operator)): Framing Fairness: A Practical Approach to Beyond-Cost Optimization for TSOs’ Mathematical Programming Problems\nGeoffrey De Smet (Timefold): How to build an open source solver and a company around it\nTomasz Stopa (IBM): Quantum computer – from holy grail to your favorite toy\n\n  \n  \n\nOrganisation committee: \nVladimir Fux\, Zalando (Germany)\, Michele Quattrone\, AirLiquide (France)\, Sander van Aken\, Flix SE (Germany)\, Torkel Haufman\, Sintef (Norway)\, Waldemar Kocjan\, Boeing (Sweden)\, Izabela Żółtowska\, Warsaw University of Technology (Poland)\, Mariusz Kaleta\, Warsaw University of Technology (Poland)\, Susanne Heipcke\, FICO (France)  chair \n\nHosted by:
URL:https://www.euro-online.org/websites/or-in-practice/event/euro-practitioners-forum-6th-annual-conference/
ATTACH;FMTTYPE=image/jpeg:https://www.euro-online.org/websites/or-in-practice/wp-content/uploads/sites/8/2025/06/Kampus_Budynki_-2.jpg
END:VEVENT
END:VCALENDAR