Women in Data Science (WiDS) Belgium was established in 2023 as an independent chapter of the global WiDS movement. Our founding member, Setareh Tasdighian, participated in WiDS Zürich for two years as a mentor and as a member of the organizing committee. The positive spirit and soulful work of that experience inspired her to bring the same movement to Belgium.
Our Mission & Vision
Our mission is to empower and inspire women in data science, promoting their leadership and advancing their careers in this dynamic field. We believe that by creating a supportive and inclusive environment, we can unlock the full potential of women data scientists and contribute to a more balanced and equitable representation in the industry.
Furthermore, we envision a future where women are equally represented and valued in the data science landscape, making significant contributions to shaping the world through data-driven insights and innovation.
Our Goals
To achieve our mission and vision, we are committed to pursuing the following goals:
Building a community of women in data science through networking events, workshops, and mentorship programs.
Promoting diversity and inclusion in the data science community by advocating for equal opportunities and challenging stereotypes.
Inspiring and educating everyone interested in data science by showing outstanding work from women.
Join Us
We invite you to join us in our mission to inspire and empower women in data science. You can support us by following us on social media, sponsoring or participating in our conference, or joining the ambassador team to organize the next event. As a leader you can encourage your team members to attend or speak at our events.
Organizers
(Click on our names to read our bio!)
Setareh Tasdighian Dr. Setareh Tasdighian is a senior postdoctoral scientist at VIB (Flemish Institute for Bioinformatics in Belgium), University of Ghent. Her current research includes developing AI algorithms for analyzing single cell transcriptomics data. She has also collaborated with GSK to analyze systems vaccinology data. Setareh is a mathematician by training and completed her Ph.D. in the mathematical modeling of evolutionary systems biology in plants. Following her Ph.D., she worked at BASF as a computational system biologist, where she applied her expertise in database management, software development, and algorithm design in biochemistry and biotechnology. PresidentEdith HeiterEdith Heiter is a fourth-year PhD researcher affiliated with the Artificial Intelligence and Data Science group at IDLab, Ghent University. She is primarily interested in dimensionality reduction and data visualization for biological data. Her vision is to make machine learning and dimension reduction algorithms more transparent and interactive, to ease result interpretation and increase data insights.
In her free time, Edith enjoys nature while cycling through Belgium or embarking on longer hikes in Europe but can also be found indoors when sewing her own clothes or baking bread. Vice PresidentSofie Goethals Sofie Goethals is a final-year PhD researcher, affiliated with the Applied Data Mining Lab at the University of Antwerp. Her research is focused on Reponsible AI, and more specifically on transparency, fairness and privacy. In her free time, she loves running, reading, meeting friends and traveling.
Speakers LeadYanou Ramon Yanou Ramon serves as a data science consultant at McKinsey Digital. She brings more than a year of experience in designing and implementing analytical solutions, and has worked in different countries on projects across different industries such as Pharma and Teleco, and on various topics such as demand forecasting and workforce optimization. Prior to McKinsey, she obtained her PhD from the University of Antwerp where she contributed to the research field of explainable AI by presenting new methods to explain black-box AI models that are built from human behavioral data. Ine Weyts Ine Weyts is currently in the second year of her six-year PhD journey at the Applied Data Mining Lab, University of Antwerp, with a primary research focus on Responsible AI, more specifically exploring counterfactual explanations. In addition to this research, Ine contributes to the teaching of the master’s courses Machine Learning, Data Science Ethics and Data Engineering at the Faculty of Business Economics. Outside academia, she enjoys socialising, swimming, reading and travelling to relax and recharge.
Kanimozhi UmaKanimozhi Uma is a Post Doctoral Fellow at the Department of Computer Science, KU Leuven, her research areas include Clinical Data Science, Multilingual Information Extraction and Machine Learning. She holds a PhD from CEG, Anna University and previously she was leading data science teams at various industries for 8+ years.
Her interests lie in Machine Learning, Knowledge Representation, Inferencing & Reasoning, Recommendation Engines, Semantic Linking, Multi-modal Deep Learning systems. She aspires to be an expert in the field of AI by building systems that can sense, comprehend and act.
