Main focus: Data Science & Trustworthy AI
Websites/Blogs/Social Media Accounts:
https://cosimameyer.com/
Languages: German, English
City: Mannheim
State: Baden-Wuerttemberg
Country: Germany
Topics: women in tech, community building, data science, women empowerment, explainable ai, computational social science
Services: Talk, Moderation, Workshop management, Interview
Willing to travel for an event.
Willing to talk for nonprofit.
Cosima Meyer is a data scientist with a strong focus on making machine learning models explainable and accessible. Passionate about trustworthy AI, she is committed to building systems that are not only technically robust but also transparent and ethical. She is a Google's Women Techmaker Ambassador and was recognized as a Futuremaker 2024 by Business Insider for her contributions to the tech community.
As the founder of R-Ladies Cologne and an active member of PyLadies, Cosima is dedicated to fostering inclusive and collaborative communities, working to bridge the two groups and create spaces for knowledge-sharing and growth. She frequently gives talks on topics such as community building, software development, and programming, sharing her insights and experiences to inspire others.
During her PhD studies at the University of Mannheim, Cosima discovered her enthusiasm for sharing knowledge through technical blog posts and developing open-source software. Her work reflects a blend of technical expertise and a passion for community building, inspiring others to explore, learn, and contribute to the fields of explainable AI and data science.
Examples of previous talks / appearances:
Women in Data Science is a worldwide initiative that brings female speakers together to give insights into the newest developments in data science ranging from academia to industry and to support women in the field.
The event was co-hosted by IBM, Stanford University, WUMAN, and the University of Mannheim.
This talk is in: English
As part of the workshop, I introduced participants to a comparison of both Python and R and demonstrated how they can leverage both in their daily data science tasks. I also wrote a blog post about it, which you can access here.
This talk is in: English
Women in Data Science is a worldwide initiative that brings female speakers together to give insights into the newest developments in data science ranging from academia to industry and to support women in the field.
The event was co-hosted by SAP Next-Gen, Stanford University, and the University of Mannheim.
This talk is in: English
Text data provides an oasis of information for both researchers and non-researchers alike to explore. Natural Language Processing (NLP) methods help make sense of this difficult data type. The talk and code gave a smooth introduction to the quanteda package. I also showcased how to quickly visualize your text data and cover both supervised and unsupervised approaches in NLP. As part of the code demo, we used text data from the UN as a working example to give you first insights into the structure of text data and how to work with it.
This talk is in: English
Research produces fascinating findings. But it is often difficult to present them to a broader audience beyond the research paper. Shiny apps offer researchers (both in academia and business) sophisticated tools to generate web applications that make the results accessible, understandable, and interactive. The talk will guide you through the necessary steps to set up your own ShinyApp and discuss lessons learned from building a ShinyApp using Shiny for R, shinydashboards, and echarts4r.
This talk is in: English
Text data provides an oasis of information for both researchers and non-researchers alike to explore. Natural Language Processing (NLP) methods help make sense of this difficult data type. The talk and code gave a smooth introduction to the quanteda package. I also showcased how to quickly visualize your text data and cover both supervised and unsupervised approaches in NLP. As part of the code demo, we used text data from the UN as a working example to give you first insights into the structure of text data and how to work with it.
This talk is in: English
Keynote delivered at NHS-R/NHS.pycom Conference 2023 (UK).
This talk is in: English