Women in Data Science and Mathematics

Increasing the visibility of female and non-binary researchers in data science and mathematics — through a monthly seminar series, research newsletter and research talk video festival.

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About us

1.1

Seminar Series

Monthly research talks by female and non-binary researchers on recent advancements in mathematics and data science — everyone is welcome, regardless of gender.

When: The last Wednesday of every month. To accommodate attendees from different regions, the seminar time may rotate.
Where: Online, via Zoom meetings.
Session: Approximately one hour: a research talk followed by a Q&A session.
Afterwards: Participants are welcome to join the informal chat with the organisers and speakers after the talk to foster interaction.

For more details, please refer to the Instructions.

Next seminar

Coming soon

Speaker: Qi Chen
Date & Time: 16:00 (GMT), November 18, 2026

The talk title, abstract and registration link will be posted soon. Stay tuned!

Upcoming events

Latest talk · October 28, 2026

Fast Bayesian Calibration of Option Pricing Models Based on Sequential Monte Carlo Methods and Deep Learning

Prof. Dr. Eva Lütkebohmert-Holtz

All past talks

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Who should we invite next?

We welcome your suggestions for future speakers in the WINDSMATH seminar series. All proposals will be carefully considered on a rolling basis when inviting upcoming speakers. If you have someone in mind, please take a moment to fill out the form — it only takes a minute.

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1.2

WINDSMATH Newsletter

In addition to our seminar series, WINDSMATH also highlights recent research by women in data science and mathematics through our newsletter. Each edition introduces a recently published paper authored or co-authored by a woman researcher in the field, providing a concise overview of the work and its scientific contribution.

Through this initiative, we hope to further increase the visibility of women researchers while sharing recent developments across mathematics, statistics, machine learning, data science, and related areas. Newsletter updates will be posted in our LinkedIn group.

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1.3

Research Talk Video Festival

An online showcase celebrating high-quality research outputs from early-career female and non-binary researchers in mathematics, machine learning, and data science. Videos that pass peer review are published on the official WINDSMATH YouTube channel.

2026 First Place: Alona Jurgenson (University of Oxford)
2026 Second Place: Mihriban Ceylan (University of Mannheim)

Festival 2026 Watch the playlist

1.4

Women in Science & Mathematics Organisations

We have also compiled a collection of organisations, networks, and communities that support and connect women in mathematics, statistics, data science, computing, and related scientific fields.

Association for Women in Mathematics
European Women in Mathematics
IMU Committee for Women in Mathematics
Caucus for Women in Statistics and Data Science
Women in Probability
Women in Number Theory

Explore organisations

1.5

AI for Maths

A reading list on artificial intelligence and mathematics: reports, essays and news on how AI is changing mathematical research and training.

2 About

Machine learning, a powerful and data-driven technology, has been successfully used in diverse fields such as computer vision, digital health, economics and science. However, the mathematical foundation and scientific advancements in machine learning may not be as widely recognised.

The goal of “Women in Data Science and Mathematics” is twofold: on the one hand, it aims to show recent advancements in interdisciplinary research in mathematics and data science, and on the other hand, it should increase the visibility of underrepresented groups in the field by featuring high-quality research delivered by female and non-binary researchers. This approach will help to address structural bias and create role models, encouraging women to pursue research in this area.

We warmly welcome everyone to join us, regardless of gender. WINDSMATH serves not only as a platform to celebrate outstanding research achievements in data science and mathematics but also as an inclusive forum to facilitate research discussions among diverse participants for exchanging ideas and networking.

Scientific Committee & Organisers windsmath@windsmath.com