Mennatallah El-Assady earned her doctoral degree from the University of Konstanz, Germany, with a thesis entitled “Levels of Explainability for Human-AI Interaction in Visual Text Analytics.” She has also received an MS and a BS in information engineering from the University of Konstanz. Since 2021, she has been an independent research fellow at the ETH AI Center in Zurich. Her research interest lies at the intersection of data analysis, visualization, computational linguistics, and explainable artificial intelligence.
During her time at the University of Konstanz, she led a subgroup with several Ph.D. students working on the topics of visual text analytics and explainable AI. A trademark of Mennatallah El-Assady’s work is her engagement in the leadership of large-scale collaborative projects and her desire to generate impact in application areas by providing online interactive visual analytics platforms for use in a range of research disciplines.
Mennatallah El-Assady has an outstanding publication record and has published many high-impact papers in top journals and conferences. Several of them have received best paper awards and honorable mentions. Her role in the European research community is underlined by her large number of publications in the Computer Graphics Forum, through the EuroVis conference, from 2016 and onwards. Since 2021, she has been serving as a member of the EuroVis full paper program committee, and she was recently selected by the EuroVA steering committee to become a EuroVA Co-Chair for the years 2023 and 2024. Her engagement in the international community is also underlined by her work on founding two workshop series (VIS4DH, VISxAI), both of which have now become established and long-running associated events at the IEEE VIS conference.
Through her outstanding research and leadership, Mennatallah El-Assady serves as a role model for early career researchers. EuroVis is very pleased to announce her as the winner of the EuroVis Early Career Researcher Award 2023, in recognition of her outstanding contributions in data mining, machine learning, visual analytics, and human-AI collaboration with applications to computational linguistics, digital humanities, and explainable artificial intelligence.