Name: #25 Meetup Women in Machine Learning & Data Science at WMI UAM
Start: 2025-01-14T18:00:00+01:00
End: 2025-01-14T21:00:00+01:00
Location: Wydział Matematyki i Informatyki Uniwersytet im. Adama Mickiewicza w Poznaniu

For this special event, our invited speakers will come from Warsaw to share their experience with WiMLDS Poznań community!

***Zuza Kwiatkowska*** *\- On the technical side of the AI force for nearly 10 years\. For the past 2 years\, she has been translating from scientific to human through social media\, public speaking\, and trainings\. Creatively fueled by ADHD*. **[[LinkedIn](https://www.linkedin.com/in/zkwiatkowska)]**

**Inez Okulska** - *Editor-in-Chief of "hAI Magazine" - the first printed magazine on artificial intelligence in Poland, and VP of Research at CampusAI. Researcher and creator of algorithms, scientist, currently senior research engineer in the area of ​​natural language processing (NLP) at the Wrocław University of Science and Technology. By education, she is both a humanist (Polish philology, comparative studies) and an engineer (automation and robotics). She used to visit Harvard. Author of numerous speeches and lectures (including on TedX and I love Marketing), where she talks about non-human intelligence in human language. Many times distinguished in prestigious rankings, including Top100 Women in AI and Top100 Women in Data Science in PL.* **[[LinkedIn](https://www.linkedin.com/in/inezokulska)]**

**Agenda (start at 6:00 pm)**

**Event opening**
**Talks**

**1\. "The Solution to the Deepfake Problem Might Already Exist" \- Zuza Kwiatkowska**

*Deepfake technology, which can be used to create fake digital media, has become a major issue that is deeply concerning us all. The tools created by scientists give people the power to undermine someone's reputation or make false accusations with just a few clicks.*

*But is the problem really with the technology itself and the scientists who developed it? Or should we be looking more at ourselves, the users of these digital illusions?*

*Interestingly, the solution to the deepfake problem may already be out there. However, accepting and implementing this solution could be an uncomfortable and difficult challenge for us as a society.*

**2\. “When RAG Evaluation Goes Rouge: Metrics\, Dataset Preparation and Other Headaches” \- Inez Okulska**

*Evaluating Retrieval-Augmented Generation (RAG) systems often feels like navigating a labyrinth of unmet expectations, absent benchmarks, and overlooked nuances. While much of the discourse focuses on building RAG-based solutions, the real challenges emerge when trying to measure their effectiveness.*

*Constructing custom evaluation datasets is no small feat—especially in languages like Polish, where source material is often poorly digitized. Drawing from my own experience, I will offer some food for thought on the questions of what and how to evaluate in RAG-based systems, or their individual components, such as information retrieval and text generation.*

**Networking**
Pizza time by GFT

**WiMLDS Code of Conduct**
https://github.com/WiMLDS/starter-kit/wiki/Code-of-conduct

More details soon. Stay tuned!

Agnieszka Kamińska

Zuzanna Kunik

Basia

Julia Będziechowska

Martyna

Poznań Women in Machine Learning & Data Science

Technology

Artificial Intelligence

Machine Intelligence

Predictive Analytics

Data Visualization

Data Analytics

Big Data

New Technology

Robotics

Machine Learning

Gender Equality

Data Science

WiMLDS

#25 Meetup Women in Machine Learning & Data Science at WMI UAM

Wydział Matematyki i Informatyki Uniwersytet im. Adama Mickiewicza w Poznaniu

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Poznań Women in Machine Learning & Data Science

#25 Meetup Women in Machine Learning & Data Science at WMI UAM

Poznań Women in Machine Learning & Data Science

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