Dennis Schulz
TNG Technology Consulting GmbH, Senior Consultant
TNG Technology Consulting GmbH, Senior Consultant
Heidelberg, Germany
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Dennis Schulz is a Senior Consultant at TNG Technology Consulting. He holds a PhD in low temperature physics from the University of Heidelberg. Besides being a programmer, he organized and hosted the TV show Quasi Klar for RNF, published a book that was translated to Korean and Russian, and won Science Slam competitions all over Germany. As part of the Innovation Hacking team at TNG, he worked on different AI showcases, fine-tuning embeddings, and data mining.
Dennis Schulz ist Senior Consultant bei TNG Technology Consulting. Neben seiner Arbeit als Software Engineer organisierte und moderierte er die Fernsehsendung 'Quasi Klar' für RNF. Er veröffentlichte das Buch 'Goethes Faust und Einsteins Haken' im Rowohlt Verlag und gewann Science Slams in ganz Deutschland. Seine Promotion in Tieftemperaturphysik absolvierte er an der Universität Heidelberg. Als Mitglied des 'Innovation Hacking'-Teams arbeitet er an AI-Showcases, dem Fine-Tuning von Embeddings und Projekten im Data Mining.
Area of Expertise
Topics
We Downloaded Our Lives: What Companies Really Know About Us
The internet never forgets. We've all heard that before. But what does that really mean? In this talk, we show the chaos, the biggest insights and the weirdest details that come back when you invoke your European right to your own digital history.
We asked hundreds of companies for our personal data: online shops, social networks, advertisers, health insurers, dating platforms, and so many more. We received everything from hand-redacted PDFs to gigabytes of CSV and JSON files, and tried to reconstruct our online and offline lives. We turned to AI to handle the heaps of data, and before we knew it, it had assembled an almost complete biography of our lives.
In this talk, we will unpack all the datasets we got: small online shops, medium-sized tech companies, and the Silicon Valley giants. Using this data, we try to analyze our own behavior: Have we truly never ghosted anyone while dating online? Can we tell where we went on vacation ten years ago? And do we even want to know what our search history reveals? In true “what could go wrong?” spirit, we will run a live demo on our own data. Let's face the most embarrassing things companies already know about us!
Restaurants around train stations are bad and I can prove it
Does the quality of restaurants degrade with your proximity to a train station? In this culinary data exploration, we used publicly accessible data to assess whether busy train stations correlate with lower restaurant ratings - and which towns are actually the worst. Using the Google Maps API and the hottest framework for data manipulation, polars, we give an overview over publicly available data resources and show how far you can get with them.
Of course, this talk will also deliver all the cold hard food facts: Analyzing the data of over 10,000 restaurants in Germany and worldwide, we will present the best and worst dining options available at train stations. We compare urban and rural environments, examine the impact of chain stores, and provide practical advice for you, the hungry traveler. So welcome aboard this gastronomic journey, ensuring your next meal on the go is a delightful one!
Finally Understand Embeddings - And You Will Never Have to Search for the Right Emoji Again
Embeddings are the foundation of how Large Language Models understand the world. Yet, when you try to read about them, you are bombarded with scary words like tensors, matrices and multi-head attention.
No need! Let's try and actually get a grip on how Embeddings work. Join us to understand how powerful they can be as a tool for Natural Language Processing. Of course, we will bring our own demo application that adds a correct, fitting and tasteful emoji to whatever chat message you feed it with - so your parents will finally be able to pick the correct emoji when writing to you.
We will explain why we translate language into high-dimensional vectors. Then, we will build our sample application for emoji search, explaining semantic search, finetuning and multi-modal embeddings along the way. We will also give an overview over benchmarks and how to scale your semantic search application.
The Sound of Privacy – What Your Spotify Data Reveals About You
It's just a music app – but how much can one actually learn about a person when granted access to their Spotify data? In this talk, we present what we learned about our colleagues through their Spotify user data.
By leveraging the GDPR, we looked into various questions: How often do people lose or damage their phones? Where did they travel? And how regular are their sleep patterns? Alongside detailed insights into Spotify data, we provide a brief overview of the legal framework and examine how strictly other companies comply with the GDPR. While everyone in theory understands that data can hold immense power, this talk presents concrete examples – particularly given that we're dealing with what seems like just a music app.
IT-Tage Frankfurt Upcoming
Der Klang der Privatsphäre - was deine Spotify-Daten über dich verraten
Moldova DevCon Upcoming
The Sound of Privacy – What Your Spotify Data Reveals About You
NDC Oslo 2026 Sessionize Event Upcoming
WeAreDevelopers World Congress 2026 - Europe Sessionize Event Upcoming
TDWI München 2026 Sessionize Event Upcoming
TDWI München Upcoming
DevBcn 2026 Sessionize Event Upcoming
DevDays Vilnius
Finally Understand Embeddings - And You Will Never Have to Search for the Right Emoji Again
Big Data Conference
We Downloaded Our Lives: What Companies Really Know About Us
Minds Mastering Machines
Embeddings richtig verstehen
PyCon & PyData
Restaurants around train stations are bad and I can prove it
AI Lowlands 2025 Sessionize Event
data2day
Der Klang der Privatsphäre – was deine Spotify-Daten über dich verraten
BaselOne
Der Klang der Privatsphäre - was deine Spotify-Daten über dich verraten
Budapest Data+ML Forum 2025 Sessionize Event
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