WiDS Belgium is an independent event that coincides with the annual Global Women in Data Science (WiDS) Conference held at Stanford University and an estimated 200+ locations worldwide. All genders are invited to attend WiDS regional events, which features outstanding women doing outstanding work.
We are in the process of inviting speakers. If you have a recommendation on who you’d like to see, feel free to contact us!
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Program
The conference is scheduled to run for an entire day (approximately from 9:00 AM-5:00 PM) with the opportunity for informal networking afterward. We aim to include the following in our program:
Keynote presentations
Lightning talks
Mentoring session
Networking session
Panel discussion
Posters exhibition
Sponsor booths
We will keep you informed with the finalized schedule on this page and through our social media channels.
WiDS Belgium Ambassadors
(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. PR LeadIne 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.
PR and speakersChananchida (Sai)Sai was born and raised in Bangkok, Thailand. She completed her Bachelor’s degree in molecular biotechnology at Ghent University Global Campus in South Korea, and went on to pursue her Master’s degree in bioinformatics at Ghent University, Belgium. Currently, Sai is in the third year of her PhD program, where her primary research interests revolve around data analysis in the field of transcriptomics, with a particular focus on single-cell and spatial RNA-seq data. In her leisure time, Sai enjoys playing video games with friends and playing the piano.
WebsiteKanimozhi 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.
