Agenda Machine Learning Week Europe 2025
17 - 18 November 2025, Berlin
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Monday, November 17, 2025
Monday
Mon
8:00 am
Monday, November 17, 2025 8:00 am
Registration & Breakfast Snacks
Monday
Mon
9:00 am
Monday, November 17, 2025 9:00 am
Welcome to Machine Learning Week Europe 2025
Speaker: Martin Szugat, Founder & Managing Director, Datentreiber GmbH
Monday
Mon
9:05 am
Monday, November 17, 2025 9:05 am
Keynote: From Assistants to Agents: Building AI That Acts, Not Just Answers
Speaker: Farah Ayadi, Principal Product Manager, feedly
AI is evolving from answering questions to solving problems autonomously. This keynote reveals how to build AI agents that plan, decide, and act, transforming industries from software development to customer service. Learn practical frameworks for creating trustworthy autonomous systems, proven strategies for user adoption, and a roadmap from simple assistants to fully autonomous agents. Discover why the organizations mastering AI agents today will define the next decade of innovation.
Monday
Mon
9:50 am
Monday, November 17, 2025 9:50 am
Sponsored Session
Monday
Mon
10:20 am
Monday, November 17, 2025 10:20 am
Coffee Break
Monday
Mon
10:45 am
Track 1: Business Case Studies
Monday, November 17, 2025 10:45 am
10:45 am: Scaling Video Understanding at RTL: From Content Moderation to Strategic AI
Speaker: Sandra Bystricky, AI Product Manager, RTL Deutschland
11:15 am: From Manual to Automated Author Identification: How Springer Nature Finds the Needles in the Haystacks
Speakers: Bhaswati Mukherjee, Product Manager, Springer Nature Audrey Knight, Senior Analyst, Springer Nature
Manual video review for compliance is slow and costly. To solve this, RTL built merm:ai:d – a modular AI platform for automated video understanding, classification, and enrichment. It has reduced moderation times by up to 80% and unlocked new automation potential. This session shows how RTL designed scalable AI workflows that evolved from a single use case into a strategic asset – and what it takes to align AI innovation with business value in media contexts.
Track 2: Industry Case Studies
Monday, November 17, 2025 10:45 am
10:45 am: Model Predictive Control for Automated Biologics Drug Product Manufacturing at Johnson & Johnson
Speaker: Renata Pocitarenco, Scientist, Johnson & Johnson
11:15 am: From Gut Feeling to Forecast Excellence: How Krombacher Achieved Industry-Leading Demand Forecasting
Speaker: Dr. Max Schüssler, Data Scientist, Krombacher Brauerei
The presentation will focus on the justification, development and implementation of an advanced control strategy for automating the dilution process in fill-finish manufacturing. The novel strategy includes the implementation of sensors, real-time data processing and modeling, combined with immediate process feedback control. This approach was implemented at Johnson & Johnson in the commercial facilities and allows to reach the target protein concentration with high accuracy despite process irregularities.
Monday, November 17, 2025 10:45 am
Is Data Art? Using Machine Learning to Turn Data Into Beautiful Visualizations
Speaker: Dr. Christoph Best, Senior Data Scientist, Google
Understanding data is hard. Visualization techniques help us to see the meaning in data and convey it to out audience. Neural networks can be tools to extract meaning from data and turn data into beautiful representations of its underlying structures. The session will be a hands-on demonstration on how to use visualization tools from clustering over self-organizing maps to deep learning-based variational autoencoders with the aim to create meaningful and beautiful data visualizations.
Monday
Mon
11:45 am
Monday, November 17, 2025 11:45 am
Room Change
Monday
Mon
11:50 am
Track 1: Business Case Studies
Monday, November 17, 2025 11:50 am
11:50 am: Accelerating Marketing Delivery: Axel Springer’s Journey to a Unified Next-Gen Automation Platform
Speakers: Nils Paetsch, Senior Data Engineer, Axel Springer National Media & Tech Justin Neumann, Senior Data Scientist, Axel Springer National Media & Tech
12:20 pm: Personalizing Newsletter Recommendations at DIE ZEIT
Speaker: Alexander Steinke, Data Analyst, DIE ZEIT
Nils, Senior Data Engineer, and Justin, Senior Data Scientist, present a Case Study from publisher Axel Springer. They explain how isolated predictive use cases evolved into a next-gen marketing automation platform that speeds campaign delivery and drives subscriber growth. Justin covers their journey of ML use cases in marketing; Nils details data integrations that formed a unified Customer Data Chip and seamless automation platform. This session showcases a blueprint for marketing enablement.
Track 2: Industry Case Studies
Monday, November 17, 2025 11:50 am
11:50 am: From Time Series to Delivery Promises: Clustering Postal Codes Beyond Geography at Zalando
Speaker: Dr. Chiara Balestra, Machine Learning & Data Mining Applied Scientist, Zalando
12:20 pm: Scaling ML and AI in a Dynamic Supply Chain: Lessons from Wayfair
Speaker: Gaku Tobinobu, Head of Supply Chain & Service ML/AI Science, Wayfair
Tight and precise delivery promises are fundamental at Zalando. In some countries, however, our ML models led to unwished overly broad promise windows. Postal codes historically exhibit different delivery behaviors, justifying a move from a country to a regional-level. However, clustering methods are not available for partially observable time series data structures. By extracting empirical probability distributions to cluster postal codes, we obtained regions having tighter promise windows.
Monday, November 17, 2025 11:50 am
Using Generative AI and Machine Learning Methods for Retail Fraud Detection
Speaker: Dean Abbott, Chief Data Scientist, Appriss Retail
Generative AI has captured the imagination of industries worldwide, widely hailed as a catalyst for innovation and efficiency, yet adoption remains limited.
In this session, I will share how Appriss Retail combines AI approaches to address fraud and abuse in retail sales and returns. Generative AI assists analysts in exploratory data analysis and investigating organized retail crime. Meanwhile, traditional machine learning models drive real-time decisions to mitigate returns fraud and abuse
Monday
Mon
12:50 pm
Monday, November 17, 2025 12:50 pm
Lunch Break
Monday
Mon
2:00 pm
Track 1: Business Case Studies
Monday, November 17, 2025 2:00 pm
2:00 pm: Scaling Educational Content with LLMs: Evaluating LLM Generated Gontent at Cornelsen
Speakers: Omar Kassem, ML Engineer, Merantix Momentum Anna Chechulina, AI Engineer, Cornelsen Verlag
2:30 pm: How to Use GenAI to Enrich and Clean the Adeo DIY Knowledge Graph
Speaker: François Serra, ML Engineer, Adeo
In this case study, we present the collaboration between Merantix Momentum and Cornelsen to develop AI Material Designer https://www.cornelsen.de/digital/ai, a tool that uses LLMs to generate curriculum-aligned teaching content. The talk will focus on the challenge of evaluating AI-generated materials, compare manual review with LLM-as-judge approaches, and share key lessons and business insights from deploying the evaluation strategy in an educational setting.
Track 2: Industry Case Studies
Monday, November 17, 2025 2:00 pm
2:00 pm: Reinventing the Aluminum Industry: The Case of Alumil with Smiling Machines
Speaker: George Koutsoudakis, CEO, Smiling Machines
2:30 pm: LLM-Powered Extraction of Critical Mineral Data from Mining Reports at InferLink
Speaker: Dr. Goran Muric, Principal Scientist, InferLink Corporation
This session reveals how Alumil and Smiling Machines transformed a traditional industry through AI—not by starting with models, but by building the foundation first. Over three years, we reshaped culture, redefined processes, secured networks, and cleaned data flows before applying machine learning. Participants will learn that behind every AI success lies a deep transformation in mindset, systems, and continuous improvement.
Monday, November 17, 2025 2:00 pm
Machine Unlearning in Practice: Addressing Privacy and Bias in Deployed Models
Speaker: Leonardo Benitez, Machine Learning Researcher, Universidad Autónoma de Madrid
Machine unlearning – the process of removing specific data from trained models – is becoming critical to comply with regulations like GDPR and the EU AI Act, and to reduce harmful biases or errors caused by flawed data. While research has advanced, deploying unlearning techniques in production remains highly challenging. This session explores practical approaches, common pitfalls, and hands-on solutions using the Vision-Unlearning Python library.
Monday
Mon
3:00 pm
Monday, November 17, 2025 3:00 pm
Room Change
Monday
Mon
3:05 pm
Monday, November 17, 2025 3:05 pm
Towards Autonomous AI: Agentic Business Models
Speaker: Tomas Sykora, Principal Solutions Architect, Amazon Web Services
Together we’ll explore how Agentic AI is changing the way software companies create, deploy and deliver solutions. We’ll dive into business models introduced by Agentic AI, net new, emerging, but also iterative – meeting software companies half way. We’ll look what’s beyond the horizon and dive into the topic of Autonomous AI, and models enabled by this shift such as Autonomous Business Capabilities.
Monday, November 17, 2025 3:05 pm
Quantum Machine Learning: How Will Quantum Computers Change the Game
Speaker: Dr. Abel Yuste, Associate Director of Data Science, Novartis
In this visionary round table discussion, we will dive into the emergent field of Quantum Machine Learning. Venturing beyond mere prediction, we’ll explore the transformative potential of quantum computing to speed up processing, increase efficiency, and solve complex problems that are currently beyond reach. Let’s collaboratively envision a future where Quantum Machine Learning revolutionizes industries, from healthcare to IT. The conversation is far from over – it’s just beginning.
Monday, November 17, 2025 3:05 pm
Understanding Cost & Return from Data Assets – Making Informed Decisions on Data Related Investments
Speaker: Dr. Armin Arnold, Head of Data Platforms, qurix Technology
We will explore the following questions:
- What are the prerequisites for understanding the costs associated with the generation, storage, processing, maintenance, and sharing of data assets?
- Which approaches are effective and feasible in determining the value contribution of data assets?
- How can data asset valuation be integrated into organizational decision-making?
- In what ways can a solid understanding of data-related cost drivers support proactive and informed cost control
Monday
Mon
4:05 pm
Monday, November 17, 2025 4:05 pm
Coffee Break
Monday
Mon
4:30 pm
Track 1: Business Case Studies
Monday, November 17, 2025 4:30 pm
4:30 pm: Inside Amazon’s GenAI: Practical Steps to Real Impact
Speaker: Atharva Amdekar, Applied Scientist, Amazon
5:00 pm: Adoption of GenAI at PAYBACK: From Custom Agents to Scalable Enterprise Solutions
Speakers: Dr. Alexander Khachikyan, Principal AI & Data Scientist, PAYBACK Dr. Falko Trischler, Director Data Science & Machine Learning Engineering, PAYBACK
GenAI is reshaping retail among many other industries. This session will offer an invaluable look into Amazon’s real-world GenAI integration, moving beyond theory to share the practical triumphs and hurdles. Participants will discover tangible strategies for deploying sophisticated AI at scale and learn how to spark significant product and organizational evolution, taking away key insights on navigating integration complexities to unlock transformative customer experiences and business growth.
Track 2: Industry Case Studies
Monday, November 17, 2025 4:30 pm
4:30 pm: Emergency Response in the Oil & Gas Industry: How Chang-Prompt Enables PTTEP Smart Decision-Making in High-Stakes Scenarios
Speakers: Tasaporn Visawameteekul, Engineer, Maintenance and Inspection Solutions, PTT Exploration and Production Veerinpimol Boonyawannakul, Remote Monitoring & Diagnostic Engineer, PTT Exploration and Production
5:00 pm: Numbers, Please! - 20 Years at Yello & EnBW Between Gut Feeling and Head Decision
Speaker: Dr. Andreas Stadie, Head of Analytics & Chief Product Owner, EnBW
This session explores how at PTTEP (a petroleum exploration and production company based in Thailand) applies AI on the frontline, transforming emergency response from reactive troubleshooting to proactive, guided intervention. Chang-Prompt, an AI-powered platform that transforms crisis management by acting like an ICU triage—enabling immediate action and diagnosis. You’ll hear real business use cases, learn how AI enables faster decisions, and understand the challenges.
Monday, November 17, 2025 4:30 pm
Get EU AI Act Ready: Standards and Compliance for High-Risk AI
Speaker: Frank Stadler, Managing Director, KIVOREX GmbH
With the EU AI Act in place, achieving presumption of conformity for high-risk AI systems requires a clear strategy. This session provides a concrete overview of the current state of standardization and key harmonization efforts. Frank will examine how to apply essential standards for AI management systems, risk assessment frameworks, and conformity assessment processes. Participants will learn how to align their AI system with emerging regulatory expectations and efficiently navigate compliance.
Monday
Mon
5:45 pm
Monday, November 17, 2025 5:45 pm
Networking Reception in the Exhibition Area
Monday
Mon
7:00 pm
Monday, November 17, 2025 7:00 pm
End of Machine Learning Week Europe Day 1
Tuesday, November 18, 2025
Tuesday
Tue
8:30 am
Tuesday, November 18, 2025 8:30 am
Registration & Breakfast Snack
Tuesday
Tue
9:05 am
Tuesday, November 18, 2025 9:05 am
Welcome to Machine Learning Week Europe Day 2
Speaker: Martin Szugat, Founder & Managing Director, Datentreiber GmbH
Tuesday
Tue
9:10 am
Tuesday, November 18, 2025 9:10 am
Keynote: What has AI Ever Done for Forecasting? Anecdotes and Case Studies from the Past Two Decades
Speaker: Prof. Dr. Sven Crone, Assistant Professor // CEO & Founder, iqast
AI has been hailed a breakthrough just as often as a passing fad, but with ChatGPT it looks like it is here to stay. But does this also hold true for AI in forecasting and Predictive Anlytics? With AI the go to forecasting algorithm in Electricity Demand, Computer Server Load and Ride Sharing, it is slow to catch on in other areas. Sven will share personal case studies from Beiersdorf, Hapag-LLoyd, ABInBev etc, travelling the hype cycle twice from 2004 towards the next disillusionment post 2025
Tuesday
Tue
9:55 am
Tuesday, November 18, 2025 9:55 am
Sponsored Session
Tuesday
Tue
10:05 am
Tuesday, November 18, 2025 10:05 am
Coffee Break
Tuesday
Tue
10:30 am
Track 1: Business Case Studies
Tuesday, November 18, 2025 10:30 am
10:30 am: Responsible AI: Good Data Governance & Fair Salary Predictions @ DATEV
Speakers: Dr. Frank Eichinger, Data Scientist, Datev Susanna Wolf, Data Ethics, Datev
11:00 am: Revolutionizing Finance with AI: A Deep Dive into Novartis’ Approach
Speaker: Dr. Abel Yuste, Associate Director of Data Science, Novartis
Shaping Europe’s digital future, ethics play a decisive role in implementing the AI Act. Good Data Governance aims to achieve both, efficient data management and Responsible AI. Frank and Susanna present their federated model, where data stewards collaborate with so-called data domain owners and data scientists. Using their machine-learning-based salary-prediction tool as a case study, Frank and Susanna demonstrate how fairness can be embedded into applications, highlighting how they address challenges such as gender disparities.
Track 2: Industry Case Studies
Tuesday, November 18, 2025 10:30 am
10:30 am: Multi-agent User Interaction with GraphChat at Zeiss
Speaker: Ian Ormesher, Data Scientist, ZEISS
11:00 am: Efficient Knowledge Management at thyssenkrupp Automation Engineering
Speakers: Kai Hauffen, Staff Engineer for Digital Factory Solutions, thyssenkrupp Automation Engineering Dr. Alexander Lammers, Chief Data Scientist / Project Lead, DATANOMIQ
Zeiss developed GraphChat, a package that is being used by an increasing number of projects within Zeiss. GraphChat takes a natural language question, leverages a knowledge graph and LLM and comes back with an answer. This session addresses the limitations of traditional chatbots by enhancing user engagement and information retrieval accuracy through proactive dialogue and advanced architecture. Learn about the Planner and Executor Multi-Agent architecture, the role of Knowledge Graphs in improving context-awareness and the capabilities of GraphChat in executing precise queries.
Tuesday, November 18, 2025 10:30 am
From Zero to Hero: Multi-Agent Collaboration Patterns and MCP
Speaker: Tomas Sykora, Principal Solutions Architect, Amazon Web Services
This tech deep dive will take you from zero to a level of understanding of Agentic AI, multi-agent collaboration and Model Context Protocol (MCP) that enables you to start building own use-cases right away. Tomas will start with the simplest examples and ends up with advanced multi-agent collaboration patterns such as SWARM (compete), and GRAPH (collaborate) utilizing open source standards and libraries such as MCP, and Strands Agents SDK.
Tuesday
Tue
11:30 am
Tuesday, November 18, 2025 11:30 am
Room Change
Tuesday
Tue
11:35 am
Track 1: Business Case Studies
Tuesday, November 18, 2025 11:35 am
11:35 am: Why Transparency and Performance Need Not Be in Conflict: the Case of the Schufa-Score
Speaker: Dr. Niklas Keller, Decision Consulting & Decision Process Design, Niklas Keller Consulting
12:05 pm: AI-powered Consumer Loan Pricing at ING
Speaker: Katharina Wenzel, Senior Data Scientist & Machine Learning Engineer, ING
The assumption, that modern, complex models automatically outperform older, simpler ones, still permeates many organisations and decision-makers. Niklas will show analytically (using Bias-Variance Trade-Off and the interpolation threshold) when this holds true and when simple, transparent models perform as well or better than the most sophisticated modern AI tools. He will showcase how he used this approach to design a new, fully transparent, high-performance credit score with the Schufa Holding AG.
Track 2: Industry Case Studies
Tuesday, November 18, 2025 11:35 am
11:35 am: How an AI Assistant Simplifies Everyday Work at Otto Group
Speaker: Nora Beiteke, IT Consultant, Hermes Germany GmbH
12:05 pm: AI Transformation with a Chatbot at FUNK - How to Get Going in the Insurance Industry
Speaker: Wiebke Apitzsch, Chief Transformation Officer, AI.IMPACT
Introduction of an AI assistant for 3,000 employees at Hermes (Otto Group). 75% of users save over 30 minutes per week through this assistant. Questions addressed during the lecture: how do I successfully implement an AI assistant? How do I communicate and train? What application cases are available? What should be considered in terms of data protection and compliance? AI assistant similar to M365 Copilot and ChatGPT. Experienced speaker, e.g., Swiss Online Marketing & IFS Ultimo Customer Day.
Tuesday, November 18, 2025 11:35 am
Open Source RAG Blueprint for Document Analysis at the Example of Bundestag Speeches
Speaker: João-Marcelo Tozato, Machine Learning Engineer, FELD M
Querying specialized data like parliamentary records is crucial. This session introduces FELD M’s RAG Blueprint, an open-source framework for building production-ready RAG systems. João will showcase its application at the example of German Bundestag speeches. You’ll learn how to develop scalable and observable RAG solutions. Key takeaways include a practical path to deploying robust RAG for complex Q&A and the value of a comprehensive, production-ready framework.
Tuesday
Tue
12:35 pm
Tuesday, November 18, 2025 12:35 pm
Lunch Break
Tuesday
Tue
1:30 pm
Track 1: Business Case Studies
Tuesday, November 18, 2025 1:30 pm
1:30 pm: Unmasking Fraud: How Graph Neural Networks Decode Complex Relationships in Trustpilot Reviews
Speakers: Dr. Tudor Dascalu, Data Scientist, Trustpilot Dr. Jia Qian, Senior Data Scientist, Trustpilot
2:00 pm: AI Agents & Custom LLMs for Extracting Features from Complex Contracts at Linklaters
Speakers: Rohit Kewalramani, Principal Data Scientist, Linklaters Salim Feghali, Head of Data Strategy & Governance, Linklaters
Graph structures effectively model complex relational data across many domains. Tudor and Jia demonstrate the application of Graph Neural Networks (GNNs) on fraud detection in Trustpilot by modeling the intricate relationships between businesses and consumers. Their work showcases how GNNs can capture the complex patterns of fraudulent activities that traditional methods often miss. Additionally, they discuss model explainability, ensuring that the learnings of our GNN align with domain expertise.
Track 2: Industry Case Studies
Tuesday, November 18, 2025 1:30 pm
1:30 pm: edding: Bridging the AI-UX Gap in B2B SaaS through Interdisciplinary Collaboration
Speaker: Klaus Breyer, Head of Product & Technology, klaus-breyer.de
2:00 pm: PromptOps at TrustPilot: Operationalizing Domain Intelligence with Multimodal GenAI
Speakers: Michelangelo Giorgi, Data Science Manager, Trustpilot Yangfan Zhanglin, Data Scientist, Trustpilot
Machine Learning adds complexity to product design—not just in implementation, but even more during product discovery, where user value is explored. At edding, the easycheck team transformed to an empowered product team, collaborating across disciplines by rethinking roles, rituals, and structures. This session shares insights on making ML research and implementation a first-class citizen and enabling product managers and designers to work with uncertain model outputs.
Tuesday, November 18, 2025 1:30 pm
Building Agentic AI Applications: Leveraging Both Proprietary and Open Source LLMs
Speaker: Shekhar Khandelwal, Senior Data Scientist, Funnel
Agentic approach represents the future of AI application development. Learn effective methods for creating AI agents that utilize both proprietary and open source LLMs, accompanied by practical demonstrations showing these agents collaborating to solve real industry challenges. The tech showcase will feature n8n as a low-code AI agents platform alongside Agno and CrewAI frameworks for Python-based AI agents. Also learn about vendor and custom built MCP servers & integrate it with AI Agents.
Tuesday
Tue
2:30 pm
Tuesday, November 18, 2025 2:30 pm
Room Change
Tuesday
Tue
2:35 pm
Track 1: Business Case Studies
Tuesday, November 18, 2025 2:35 pm
2:35 pm: Forecasting Public Expenditure (BAföG) Using LSTMs: A Multi-Task Learning Approach for Volatile Data
Speaker: Marlene Scherer, Academic Researcher, Fraunhofer-Institut für Angewandte Informationstechnik (FIT)
3:05 pm: Who Will Be in the Bundestag? - A Bayesian Approach to Election Forecasting in Germany
Speaker: Mira Klein, Senior Data Scientist, INWT Statistics
Accurately forecasting expenditures is crucial for budgeting and policy planning. This session presents a multi-task LSTM model designed to predict annual federal student aid (BAföG) expenditures for the current and next two years. Using 16 state-level time series, it addresses extreme intra-year volatility, strong seasonality, and the risk of overfitting with small datasets. Attendees will gain insights into overcoming these challenges and improving real-world time series forecasting models.
Track 2: Industry Case Studies
Tuesday, November 18, 2025 2:35 pm
2:35 pm: A Global Voice Assistant for E-Cars: How NIO Leverages Machine Learning for Enhanced User Experience
Speaker: Dr. Olga Khryapchenkova, Lead Product Manager - AI Voice Assistant, NIO
3:05 pm: Optimizing Patient Flow: How to Harness Probabilistic Models for Discharge Planning
Speaker: Richard Levesque, Director - Advanced Health Analytics and Forecasting, Vitalite Health Network
This talk will highlight how the electric car manufacturer NIO leverages machine learning to develop NOMI, the world’s first in-vehicle artificial intelligence. The session will share lessons learned from integrating LLMs into the existing voice assistant architecture, including the challenges and opportunities this integration has presented for both the product and the organization.
Tuesday, November 18, 2025 2:35 pm
Can Compressing Foundation Models Be as Easy as Image Compression?
Speaker: Patrick Putzky, Senior Machine Learning Researcher, Merantix Momentum
Post-training model compression is a powerful way to make Large Language Models accessible in resource-constraint environments. Oftentimes, however, practitioners find themselves adjusting their needs to a set of predefined compression parameters, rather than the other way round. In this talk, I will advocate for model compression that aims to be as simple as image compression: enable users to choose a model size that fits their own needs.
Tuesday
Tue
3:35 pm
Tuesday, November 18, 2025 3:35 pm
Coffee Break
Tuesday
Tue
4:00 pm
Tuesday, November 18, 2025 4:00 pm
Presentation of the Key Take-Aways from Table Discussions
The Table Captains present the three key take-aways from their discussion round.
Tuesday
Tue
4:45 pm
Tuesday, November 18, 2025 4:45 pm
Wrap Up
Speaker: Martin Szugat, Founder & Managing Director, Datentreiber GmbH
Tuesday
Tue
5:00 pm
Tuesday, November 18, 2025 5:00 pm