Applied AI Stories: Solving Cold Cases and Powering Product Search

About this event

⚠️ Important Note:
PyData Amsterdam is transitioning to Luma. ✨

• Please subscribe to PyData Amsterdam on Luma: https://luma.com/pydataamsterdam
• And register at the Luma registration link for this event: https: https: //luma.com/bm0o8s4r

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PyData Amsterdam is back with another evening of inspiring talks, food, and networking on Thursday the 26th of March, from 17:30 until 21:30 CET at ML6 in Amsterdam! Join us for an exciting meetup where we explore how modern machine learning systems are being applied to real-world problems at scale - from cold case investigations to large-scale e-commerce search. We’ll kick off with drinks and networking, followed by two in-depth technical talks from industry practitioners, with plenty of time to connect over food and drinks afterwards.

Schedule

• ​17.30 – 18.00: 🥤 Welcome & Networking
• ​18.00 – 18.15: ML6 / HR introduction
• ​18.15 – 19.00: 🎤 Talk 1 – Can AI agents help solve Europe’s Largest Cold Case? - By Titus Naber
• ​19.00 – 20.00: 🍕 Food & Networking
• ​20.00 – 20.45: 🎤 Talk 2 – From Keywords to Concepts: A Late Interaction Approach to Semantic Product Search on IKEA.com - By Amritpal Singh
• ​20.40: 21.30: 🥤 Drinks & Networking​

Talk 1: Can AI agents help solve Europe’s Largest Cold Case?

​by Titus Naber
​The Olof Palme investigation lasted 34 years and resulted in one of the largest police archives in modern European history. Even reading the digitized portion alone would take a single person years.
​So what happens when you give that archive to AI agents?
​In this talk, Titus will walk us through the design and deployment of a Deep Research agent system capable of autonomous hypothesis generation, iterative search, and cross-referencing across thousands of police documents. The session will dive into how AI agents can be orchestrated to explore massive, unstructured datasets and support complex investigative workflows.

​Bio
Titus Naber is a Machine Learning Engineer at ML6, based in Amsterdam. He holds an MSc in Artificial Intelligence from Delft University of Technology and has experience across machine learning, full-stack development, and autonomous systems. Previously, he worked at Adyen on open-source payment integrations and was involved in autonomous racing through the Formula Student team. Titus combines strong academic foundations with hands-on industry experience to build practical, high-impact ML systems.
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Talk 2: From Keywords to Concepts: A Late Interaction Approach to Semantic Product Search on IKEA.com

​by Amritpal Singh
​Traditional keyword-based search struggles to capture the rich, multi-attribute intent behind customer queries. In this talk, Amritpal will present IKEA’s journey from keyword matching to concept-based semantic search using a late-interaction retrieval model.
​Instead of relying on Boolean logic or single-vector embeddings, this approach uses token-level scoring to preserve keyword specificity while capturing fine-grained intent. The system is trained using large-scale synthetic query generation, strong negative mining, and adaptive ranking — all while maintaining low latency at production scale.
​Deployed live on IKEA.com across multiple markets and languages, the new system outperformed the existing Boolean search, delivering meaningful gains in relevance, engagement, and commercial impact, especially for long-tail queries.

​Bio
Amritpal Singh is a Senior Data Scientist at IKEA Amsterdam with over 10 years of experience in machine learning, computer vision, and NLP. Previously, he was a Staff Data Scientist at Huawei and a Senior Research Engineer at HERE Technologies. He holds an MSc in Embedded Systems from TU Delft and a BTech in Electrical Engineering from Vellore Institute of Technology.
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We look forward to welcoming you for an evening of cutting-edge ML, practical insights, and great conversations - see you there!