From advanced search engine technology to maintaining privacy in the analysis of Big Data: Computer scientist Monika Henzinger is working on the further development of the fundamental structures of our digital systems. At the same time, however, she makes sure that her approaches remain practical and efficient, so they can quickly find their way into practice and give rise to new applications.

In the late 1990s, California’s Silicon Valley was the scene of a technology race. Powerful search algorithms were needed that could sift through the internet's increasingly large and confusing mountain of data to provide users with truly relevant results. In 1998, computer scientist Monika Henzinger was working in a research lab in Palo Alto on the further development of Alta Vista, which was the best-known search engine at the time. In one of her papers at the time, she showed that in automated searches, focusing on the search text alone may not be the best solution. Factoring in the structure of the internet, i.e. the links between content, would increase the accuracy of the results by nearly 50%, she found.

A recent start-up that was just setting up shop in Palo Alto at the time was taking exactly the approach Henzinger described: Google. They were integrating the internet’s hyperlink structures into searches, which clearly yielded better results. However, Alta Vista could not change its technology. Henzinger joined Google’s research department in 1999 to work on search algorithms, and took over as director of the department in 2001. She helped develop the principles of searching the internet that continue to impact the daily lives of hundreds of millions of people today. Her 1998 study at Alta Vista, “Improved Algorithms for Topic Distillation in a Hyperlinked Environment,” was honored with a “Test of Time” award as recently as 2014. This award recognizes work that has had a lasting impact on research in a scientific discipline.

In a nutshell

Monika Henzinger specializes in the design of algorithmic systems, including in the area of big data analysis. Her research focuses include computational verification, algorithmic systems based on graph theory, distributed and parallel computing, and algorithmic game theory. A more recent research area is differential privacy, which strives to ensure that data analysis can be done without compromising the privacy of individuals in the dataset.


Picture of Monika Henzinger
Computer scientist Monika Henzinger researches privacy protection when accessing data sets. The FWF’s international Wittgenstein Jury considers her work particularly innovative, effective, and well regarded in the highest-level academic and industrial communities. © FWF/Daniel Novotny
Screen with programming code
In data processing, saving resources is key. In most cases, attempts are made to minimize computing time and memory. Research into efficient algorithms and data structures is trying to find entirely new ways to understand how to conserve these resources – for example, by designing better algorithms. © Markus Spiske/Unsplash

Henzinger is a theoretical computer scientist and basic researcher. At the same time, her years in what was then the “new economy” of the internet allowed her work to become more application-oriented. Over the course of her career, she has delved into a wide range of different research topics within her field. But her main focus has always been on gaining a fundamental understanding of the structures and organizational forms of changing data sets and designing more efficient algorithms to interact with and use that data. In many ways, her basic research has helped create the digital systems that now affect the everyday lives of so many people.

Prior to her time in Silicon Valley, Henzinger studied the then-new field of dynamic graph theory in the 1990s. Dynamic graphs can be thought of as networks that have diverse connections between their nodes. However, these connections can change over time, so calculation approaches have to be able to cope with this changeability.

Dynamic graphs can include, for example, road maps showing current traffic jam information, or a social network that recommends “nearby” people to users who may know them – applications that were to become very relevant in the decades to come. Henzinger’s work set a “speed record” at that time. No other research approach available at that moment could compute the connectivity components of dynamic graphs as quickly as Henzinger’s algorithms. Her efficient solution was to have a significant impact on the theoretical foundations of this branch of computer science.

In addition to dynamic graphs and the information retrieval function of search engines, algorithmic game theory is also one of Henzinger's research interests. This field of study aims to better understand and analyze auctions. Here, too, search engines came into play as a potential application: Google holds a type of auction every time you place an ad. The algorithms analyze the advertising companies’ offers and select winners, whose ad is then played out in the search results.

Henzinger’s most recent research focuses on algorithms that are designed to provide the fastest possible solutions to a problem, especially with regard to the analysis of large amounts of data. In the future, for example, public sector or medical databases should also be made more accessible for scientific use. This depends, however, on being able to protect the privacy of the people depicted in this data. Inadvertent disclosure of identities must also be able to be ruled out with a very high and demonstrable degree of probability. This can be achieved, for example, by introducing a well-calculated amount of randomness or intentional variation into the data.

Short bio

Monika Henzinger was a professor at the University of Vienna from 2009 to 2022 and has been conducting her research at the Institute of Science and Technology Austria since 2023. After studying computer science in her native Germany, she earned her doctorate at Princeton University in the US and worked at Cornell University as an assistant professor. A temporary switch to the private sector culminated in Henzinger’s position as Director of Research at Google. She has authored over 200 academic papers and holds over 80 patents. Her numerous research awards include two Advanced Grants from the European Research Council ERC and the FWF Wittgenstein Award.


It’s hard to overlook Monika Henzinger's enthusiasm for her subject. The computer scientist has had a remarkable international career, including working in the private sector as director of research at Google. Back in academia, she moved from Switzerland to Vienna in 2009.
Henzinger is involved in the development and analysis of algorithms, and has most recently turned her focus to the security of private data. As a successful woman in a male-dominated field, the researcher is also committed to equality and the advancement of women.

This “noise” in the data makes sure that an individual cannot be identified based on their specific characteristics. At the same time, it also guarantees that any statistical evaluations of the data are correct with a very high degree of accuracy. Completely anonymized analyses like this are certain to play an important role in the future. It is also important that performing these calculations should not be overly difficult or complicated. “For algorithms to work, they have to be simple and effective,” Henzinger says. “Protecting privacy in the realm of Big Data is a real-world problem that really needs to be solved.”

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