Henzinger_Monika Group
Algorithms
The research field of efficient algorithms and data structures seeks to understand how to save computing resources, both by designing better algorithms and by proving bounds on the limits of possible savings. Differential privacy, on the other hand, seeks to design and analyze algorithms that compute statistics over datasets while preserving the privacy of each individual data item.
The Monika Henzinger group is interested in developing algorithms by pursuing two research directions:
(1) Efficient algorithms, especially in settings where the input changes incrementally. This applies to problems such as maintaining clusters—sets of points that are close to each other—in changing point sets as well as maintaining properties in networks that are incrementally modified.
(2) Responsible computing, especially differential privacy. Differential privacy is a way to share information about data (such as information about individuals) while disturbing the information enough to protect the privacy of the individuals. The M. Henzinger group studies differential privacy specifically in the context of dynamically changing inputs and in settings where the data is distributed over many users or databases.
Group Leader
Administrative Support
Team
Current Projects
Efficient combinatorial algorithms and data structures, especially in settings where the input changes incrementally | Responsible computing, especially differential privacy
Recent Publications
Dhulipala L, Henzinger M, Li GZ, Liu QC, Sricharan AR, Zhu L. 2025. Near-optimal differentially private graph algorithms via the Multidimensional AboveThreshold Mechanism. 33rd Annual European Symposium on Algorithms. ESA: European Symposium on Algorithms, LIPIcs, vol. 351, 91. View
Henzinger M, Kosinas E, Münk R, Räcke H. 2025. Efficient contractions of dynamic graphs – with applications. 33rd Annual European Symposium on Algorithms. ESA: European Symposium on Algorithms vol. 351, 36. View
Henzinger M, Safavi Hemami R. 2025. Securing dynamic data: A primer on differentially private data structures. 33rd Annual European Symposium on Algorithms. ESA: European Symposium on Algorithms, LIPIcs, vol. 351, 2. View
El-Hayek A, Hanauer K, Henzinger M. 2025. On b-matching and fully-dynamic maximum k-edge coloring. 4th Symposium on Algorithmic Foundations of Dynamic Networks. SAND: Symposium on Algorithmic Foundations of Dynamic Networks, LIPIcs, vol. 330, 4. View
Henzinger M, Sricharan AR, Steiner TA. 2025. Differentially private continual release of histograms and related queries. The 28th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 258, 1990–1998. View
ReX-Link: Monika Henzinger
Career
Since 2024 Vice President for Technology Transfer, Institute of Science and Technology Austria (ISTA)
Since 2023 Professor, Institute of Science and Technology Austria (ISTA)
2009 – 2023 Professor, University of Vienna
2005 – 2009 Professor, EPFL, Switzerland
1999 – 2005 Google
1996 – 1999 Digital Equipment Corporation
1993 – 1996 Assistant Professor at Cornell University, USA
1993 PhD Princeton University, USA
Selected Distinctions
2024 Best paper Award at the Symposium on Discrete Algorithms
2021 Wittgenstein Award
2021 ERC Advanced Grant
2019 Stanford University Distinguished Visiting Austrian Chair
2019 Carus medal of the German Academy of Sciences Leopoldina
2018 Science Award of the City of Vienna
2017 SIGIR Test of Time Award
2017 Member of the Austrian Academy of Sciences
2016 Fellow of the Association of Computing Machinery
2014 Member of the German Academy of Sciences Leopoldina
2014 Fellow of the European Association of Theoretical Computer Science
2014 ERC Advanced Grant
2013 Honorary Doctorate of the Technical University of Dortmund, Germany
2013 Member of the Academia Europaea
2004 European Young Investigator Award of the European Science Foundation
2001 Top 25 Women on the Web Award
1995: CAREER Development Award of the National Science Foundation
