Sessions 2026
Machine Learning World Europe
17 - 18 November 2026 | Munich
Check out the first sessions below
More sessions will be published soon
17 - 18 November 2026 | Munich
Check out the first sessions below
More sessions will be published soon
Speaker/s:
Eduardo Sepulveda, ING BelgiumA Factory Approach to Churn Identification in Banking at ING
Summary:
Why it matters: In banking, churn must be identified at scale across multiple products, under strict regulatory constraints, using interpretable models despite severe class imbalance. What we cover: how an ML factory standardizes and accelerates churn deployment while ensuring explainability and governance. Takeaways: how banks can reduce time‑to‑production and deliver controlled, measurable business impact with ML.
Speaker/s:
Dr. Felix Reinhart, MieleAI at Miele – From First AI Products to AI at Scale Across the Internet of Things
Summary:
How does Miele create customer value through AI? This talk shares key lessons learned on the journey from initial AI applications to scaling AI across a portfolio of connected appliances. It sheds light on strategic as well as technical aspects behind smart sensing, machine vision and LLM-based applications at Miele. The presentation highlights critical capabilities to deliver AI products for IoT appliances and sketches how large foundation models impact the innovation process itself.
Languages:
Table Discussions
Summary:
From the start, Machine Learning Week has been the place to discuss and share our common problems. These are your people – they understand your situation. Often rated the best part of the event, sharing your problems with like-minded professionals is your path to answers, a little empathy, and a stronger professional network. Table Discussion Topics will be announced soon. Come prepared with your problem you are solving, or a question that needs answering. And then, be ready and willing to help others in this, their hour of need.
Speaker/s:
Jyoti Yadav, MicrosoftJailbreaks, Filters and the Limits of Prompt Level Safety
Summary:
Everyone talks about jailbreaks and content filters but what stops LLM abuse when the filter fails? An attacker can make every single request look harmless while the overall pattern is clearly hostile. Drawing on a decade of hunting threat actors in cybersecurity, this session moves beyond prompt-level safety to behavioural, actor-level detection: spotting who is misusing a system, not just which prompt is bad. You will leave with a practical, layered way to think about AI safety.
Speaker/s:
Prince Tyagi, StatistaFrom Prompts to Systems: How Agentic AI Patterns Enable Reliable Data Workflows
Summary:
Most companies have data spread across databases, APIs, and reports. Answering a real business question means pulling from all of them at once. This session shows how AI agent patterns – Planner, Aggregator, and Verifier and turn that chaos into reliable answers. I will build a working demo live. Participants learn how to design agent systems, not just prompts. Key questions: When should humans review agent output? How do you handle conflicting sources? What makes an agent production-ready?
Speaker/s:
Ari Joury, Wangari GlobalSoccer Analytics: Traceable and Honest Forecasting Across a Bundesliga Season
Summary:
Forecast the Bundesliga ranking this season, and the outcome of every match. But no black boxes allowed: here’s how to model under football-level uncertainty, honestly and traceably. You’ll learn to predict matchdays with a model whose every prediction traces back to its drivers, calibrate its confidence, and watch it drift as form, injuries and transfers play out. (This same discipline that keeps a model honest in football keeps it trustworthy once it leaves demo stage at your company.)
Speaker/s:
Dr. Falko Trischler, PAYBACKHow PAYBACK Integrated Search: Hybrid Search & the “Pointy” AI Chatbot
Summary:
PAYBACK’s integrated search system combines hybrid search with ‘Pointy,’ our AI chatbot, enabling users to discover partners, coupons, and rewards, or receive instant answers to their questions across the entire PAYBACK ecosystem. This deep integration within our platform showcases an innovative application of AI in e-commerce. Our presentation will cover both the development of a highly scalable AI agent and the engineering loop that ensures its reliability and improvement in production.
Speaker/s:
Orr Shahar, Merantix MomentumExplainable Graphs: Utilizing ML to Understand Complex Manufacturing Processes at CeramTec
Summary:
How do you use ML to really understand your manufacturing process? Complex processes are hard to model – everything affects everything, and standard models struggle to capture that full chain of effects. In this talk, we show how CeramTec and Merantix Momentum tackled this at the ML level: After transitioning the shop floor to be data-first, we used Explainable Graphs to predict outcomes mid-process and give decision-makers a granular view of what drives what across the line.
Speaker/s:
Dr. Sebastian Wernicke, OxeraData Inspired: Transforming the Business. Not Just the Technology.
Track:
Summary:
On paper, we have never been more data-driven. But the day-to-day culture of many organizations—the habits, the gut instincts, the questions leaders think to ask—often struggles to keep pace. The key to true business transformation is ensuring that decision-making actually matches the power of the technology behind it. In this keynote, based on his book Data Inspired, Sebastian Wernicke reveals how to bridge the gap between brilliant technology and daily operations.
Speaker/s:
Rohit Agarwal, BizomAgentic AI Clinic: What’s Keeping Your AI Stuck in POC?
Summary:
Most Agentic AI initiatives never make it beyond impressive demos. This interactive clinic uncovers the technical, architectural, and organisational roadblocks that prevent production success. Through real-world examples and practical diagnostics, participants will learn how to identify failure patterns, design production-ready AI systems, and apply proven principles to build reliable, scalable, and trustworthy Agentic AI.