Women* in Data Science 2025

In 2016, the United Nations designated 11 February as the International Day of Women and Girls in Science, aiming to foster gender equality within STEM fields. Despite possessing equal capabilities, the global average indicates that only approximately 35% of STEM graduates are women*. Ensuring a diverse representation in science is essential to prevent a narrow perspective and to stimulate the emergence of new ideas, talents, and creativity.

Within our research network, we take pride in supporting and showcasing the pioneering efforts of female* researchers who are pushing the boundaries of their respective fields, making substantial contributions to the scientific community. Join us in commemorating the accomplishments of female* researchers, as we strive to raise awareness and inspire more women* to pursue careers in STEM.

The University of Vienna is uniting to celebrate Women* in Science through a collaborative campaign involving:

  • Computer Science
  • Mathematics
  • Physics
  • Chemistry
  • Earth Sciences, Geography and Astronomy
  • Life Sciences
  • Microbiology and Environmental Systems Science
  • Max Perutz Labs
  • Research Network Data Science @ Uni Vienna

By uniting various faculties, centres, and networks, the University of Vienna highlights the significance of diversity in science and emphasises the fundamental role of women* in advancing the field.

Find out more about the campaign:

The following is a list of remarkable women* who are active in data science and a brief overview of their accomplishments:

From left to right:
  • Edina Marica, Master Student in Data Science, is interested in machine learning and theory of algorithms, with a focus on graphs. Photo © private
  • Yllka Velaj, Assistant Professor for Computer Science, focuses on designing algorithms for graph mining. Photo © private
  • Christa Cuchiero, Professor for Quantitative Risk Management, is doing research at the intersection of stochastic analysis, machine learning, and mathematical finance. She is especially interested in classes of universal stochastic processes, approximation theory in dynamic situations, data driven risk interference, and machine learning in finance. Photo © private
  • Diana Széliová, Post-Doc Researcher at the Research Group Biochemical Network Analysis, investigates cell biology and evolution with mathematical models of metabolism. Photo © Christoph Kawan

From left to right:
  • Rebecca Kahn, Post-Doc Researcher in Digital Humanities, investigates how knowledge is transformed and transmitted when large-scale collections of digitised museum data are published and shared online. Photo © Ralf Rebmann
  • Ana Stanusic, Prae-Doc Researcher in Data Science, focuses on improving the understanding of data quality through data visualisation and including domain knowledge in data quality analysis in the field of fleet management. Photo © private
  • Stefanie Brandstetter, Prae-Doc Researcher in the Research Group Biochemical Network Analysis, focuses on the application of chemical crosslinking and mass spectrometry towards characterising conformational changes of complexes and profiling of protein networks. Photo © private
  • Laura Lotteraner, Prae-Doc Researcher in the Research Group Visualization and Data Analysis, focuses on understanding environmental issues concerning ground and surface water and its polution using data visualisation and modern data analysis approaches. Photo © Stephanie Scholz 

From left to right:
  • Claudia Plant, Professor for Data Mining, focuses on extracting knowledge from massive data. Photo © Barbara Mair
  • Tara Andrews, Professor for Digital Humanities, explores how we can take advantage of data methods and digital collections to learn new things about medieval history, even when our data and collections have a lot missing. Photo © Ilse Herzinger
  • Eva Szilagyi, Post-Doc Researcher in Theory and Applications of Algorithms, is interested in design of fast dynamic geometrical algorithms. Photo © private
  • María José Rimón Martínez, Prae-Doc Researcher at the Research Group Biochemical Network Analysis and part of the PROHITS Doctoral Network, focuses on developing genome-scale metabolic models (GEM) of thermophilic prokaryotes for study as microbial cell factories. Photo © private

From left to right:
  • Sylvia Kritzinger, Professor for Methods in the Social Science at the Department of Government, collects and analyses survey data to examine public opinion and electoral behaviour. Photo © private
  • Andrea Graf, Master Student of Bio Data Science, focuses on mathematical modelling of biotechnical processes. Photo © private
  • Yseult Héjja-Brichard, Post-Doc Researcher in the Fusani Lab at the Department of Behavioral and Cognitive Biology, focuses on sexual signals and courtship behaviours in birds and fish using deep learning and machine learning methods. Photo © private
  • Tatyana Krivobokova, Professor for Statistical Methods, is a statistician working both on applied and theoretical problems. Photo © Caro Hoene