KLOSTERNEUBURG, Austria — Computer scientist Monika Henzinger has been named the 2027 recipient of the Royal Society Milner Award and Lecture for research spanning algorithms, data structures, web information retrieval and privacy.
The Institute of Science and Technology Austria announced the award on 27 August. The Royal Society’s annual distinction recognises major contributions to European computer science and includes a medal, a £5,000 award and a lecture in London.
Henzinger’s research addresses how computational systems can process and retrieve information efficiently. Her more recent work includes responsible computing and differential privacy—methods designed to extract useful patterns from data while reducing the risk of exposing information about individuals.
That field has become increasingly important as companies train artificial-intelligence models on very large datasets. Removing names is not always sufficient to protect users because records may be reidentified through combinations of other details. Differential privacy introduces mathematically defined protections intended to limit what a system reveals about any one person.
The Royal Society cited Henzinger’s lasting impact in both academic and industrial research. She previously served as Google’s first director of research and has held academic positions at the University of Vienna and the École Polytechnique Fédérale de Lausanne.
At ISTA, she leads a research group and serves as vice-president for technology transfer. In May, the Association for Computing Machinery also selected her as its 2026–27 Athena Lecturer, an honour awarded to a woman who has made fundamental contributions to computer science.
Awards cannot resolve women’s underrepresentation in computing on their own. Their value increases when institutions also examine recruitment, promotion, conference participation, research funding and the distribution of credit within collaborative work.
Visibility nevertheless matters because computing’s public history is often presented through a narrow group of male founders and executives. Henzinger’s career demonstrates another route: foundational research moving between universities and industry while remaining connected to questions of privacy and public responsibility.
Her recognition arrives as AI companies make increasingly ambitious claims about data. The most useful celebration of her work is therefore not symbolic. It is a reminder that computational efficiency and privacy protection must be designed together—not treated as competing priorities after a system has already been deployed.
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