Vienna Data Science Group Meetup

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About us

The Vienna Data Science Group [VDSG - www.vdsg.at] is a nonprofit association which aims to promote knowledge about data science methods/techniques and AI

In its focus are:

• Applications where these methods such as machine learning (ML) are used

• New research happening in this field like deep learning

• Impact on society e.g. the introduction of autonomous cars

The Vienna Data Science Group [VDSG] rests on four fundamental pillars.

• Knowledge sharing

• Education

• Impact on society

• Fostering of ideas for business applications

How do we bring that to life?

• Holding talks and seminars for knowledge sharing and networking
• Organizing workshops bringing together companies, start-ups and data scientists
• Doing hackathons to delve into various topics like Julia or machine learning
Networking with like-minded organizations
For past meetings look at: https://metalab.at/wiki/Vienna_Data_Science...
As well as https://www.youtube.com/c/ViennaDataScienceGroup/videos

Upcoming events

See all

GEO & AI Search + Neurosymbolic AI for Industrial Data
Fri, Nov 20 · 6:00 PM CET
T-Center, Rennweg 97-99, 1030 Wien, Austria, Wien, AT
Dear Data Enthusiasts,

We're excited to welcome you on 20 November at Magenta Telekom for an evening of two great talks: how AI search is changing the way brands get found, and how knowledge graphs and AI agents turn scattered industrial data into real insight. Stay afterwards for the open mic, food, drinks and plenty of time to connect with fellow data enthusiasts!

How AI Search Is Rewriting the Buyer’s Journey
Speaker: Klaus-M. Schremser, Co-Founder & CRO at OtterlyAI
Search is shifting from short keyword queries to conversational questions. Instead of comparing a list of links, users increasingly receive a short list of recommended brands from AI assistants such as ChatGPT, Gemini or Google AI Mode.
This talk looks at what that means for how brands are discovered and evaluated, and how the effect can be measured. It draws on OtterlyAI's customer data and on 30+ experiments in Generative Engine Optimization (GEO), covering around 200M AI citations.
The session covers the rise of zero-click search, the role of third-party sources in what AI systems cite, and the limits of web analytics when attributing AI-driven traffic. It also presents technical and content measures tested in the experiments and closes with practical first steps for engineering and data teams.
About the speaker
Klaus-M. Schremser has been building software companies since 1999, with three exits along the way. He co-founded Wikidocs, whose real-time collaboration technology was acquired by Atlassian, the company behind Jira and Confluence. Today, he is co-founder and Chief Revenue Officer of OtterlyAI, a Vienna-based AI search monitoring platform. OtterlyAI tackles a new measurement problem: understanding what AI recommends, which sources it cites, and how its answers influence what people buy.

Neurosymbolic AI and Agents for Industrial Data Intelligence
Speaker: Daniel Dobriy, AI Researcher at WU Vienna & Managing Director of Dobriy AI
Every day, industrial companies announce new factories, expand production lines, invest in infrastructure and enter new markets. These developments generate valuable information, but the relevant signals are disconnected and scattered across social media, news articles, corporate websites, public databases and various documents.
How can we transform this fragmented information into structured, reliable and actionable knowledge?
In this talk, we will explore how modern data engineering, knowledge graphs and AI agents can be combined to analyse complex industrial ecosystems. Using real-world industrial scenarios, we will look at how AI systems can identify relevant events, resolve company identities across different sources and discover relationships between organisations.
We will also look at practical data engineering challenges: data quality, entity resolution and disambiguation, provenance, hallucinations, and the trade-offs between traditional data pipelines and agentic AI approaches.
About the speaker
Daniel Dobriy is an AI researcher and lecturer at WU Vienna, working at the intersection of knowledge graphs, computational semantics, neuro-symbolic AI and industrial AI applications. His interests include connecting structured and unstructured data to build intelligent systems that solve the hardest problems.
He is also the Managing Director of Dobriy AI, which specialises in real-world industrial and business applications: scalable knowledge graph hosting, data-based AI agents and web-scale data search.

Open Mic
We are going to open up the stage after the talks for community announcements. If you'd like to announce something, open this slide deck, make sure you are signed in with a Google account, and click "View Only" -> "Request Edit Access". Explain in the text box what you want to announce, and we'll give you edit access to the slide deck.

Food & Drinks
We’ll have some food and drinks after the event.

Photos
Please note that during the event, photos might be taken and later posted on VDSG's social media page. Please notify us if you do not agree.

Food Allergies
Attention attendees with food allergies: please be aware that the food and drinks provided may contain or come into contact with common allergens, such as dairy, eggs, wheat, soybeans, tree nuts, peanuts, fish or shellfish.

Best,
The Organizer Team
100 attendees
Data Science Cafe - Biotech focus Vol 1
Fri, Dec 11 · 4:30 PM CET
42 Vienna | Digital Excellence Campus, Muthgasse 26/1. Stock, 1190 Wien, Austria, Wien, AT
The Data Science Café began in 2017 as a simple community space: a place where mathematicians, software engineers, and business professionals could meet once a month, learn together, and exchange perspectives.

Over time, it became a vibrant community. In 2022, the format returned with mentors sharing their expertise—many of whom had first joined as participants in the original sessions. That journey captured something important: communities grow when people are generous with what they know and curious about what others can teach them.

Now, the Data Science Café returns with a Biotech Focus.
Vienna has an exceptional opportunity at the intersection of data science and biotech. The city brings together scientific talent, technical expertise, strong universities, innovative companies, and organisations working across the ecosystem. Yet some of the most valuable connections are still waiting to be made.

This event series is designed to create a welcoming space for those connections. Whether you work in biotech, data science, research, software, business—or are simply curious about the field—you are welcome. Different backgrounds are not a barrier; they are the point. New ideas often emerge when disciplines meet and people learn from one another.

The Data Science Café – Biotech Focus will take place every three months, bringing together mentors, professionals, researchers, students, and curious minds to explore what this intersection can make possible.

Thank you to 42 Vienna for hosting us, and to Women in AI for recommending outstanding mentors.

Seven mentors are already confirmed, with more conversations underway. The official mentor announcement will follow on 1 November.

Save the date, and join us as we learn, connect, create, and innovate together.
64 attendees