R core team at ETH Zurich awarded the Rousseeuw Prize for Statistics in Belgium; one million USD prize to five pioneers.

R core team at ETH Zurich awarded the Rousseeuw Prize for Statistics in Belgium; one million USD prize to five pioneers.

Statistics for all: open-source pioneers win million-dollar prize | ETH Zurich

Statistics for all: open-source pioneers win million-dollar prize

The free, open-source software R has fundamentally transformed research in statistics and data science — and continues to shape the field to this day. Now the pioneers who have driven its development for some 30 years are receiving the Rousseeuw Prize for Statistics, worth one million US dollars. Among the laureates is Martin Mächler, a mathematician from ETH Zurich.

The Rousseeuw Prize for Statistics, worth one million US dollars, this year goes to the core team of the statistical programming language R.

The open-source programming language R is one of the most widely used software solutions for statistics and data analysis worldwide and is freely available.

Among the open-source pioneers to receive the award is ETH Zurich statistician Martin Mächler.

Statistics is a key to understanding reality. It helps students and researchers, as well as businesses and public authorities, to assess how reliable their results are and how well they capture and explain a given phenomenon. Those who carry out statistical data analysis today will most often turn to the programming language R — one of the most widely used programming languages in the world, and freely available as open-source software.

Since its beginnings in the 1990s, R has established itself as a common language for statistics and data analysis. It is also one of the pioneering projects in free and open-source software development. Today, researchers worldwide have access to the core software as well as some 23,000 extension packages available online — with the result that there is barely a field of research in which R is not used.

In biology and medicine, for example, R forms the foundation of Bioconductor, the software used by laboratories worldwide for DNA and cancer research. During the Covid pandemic, R served as a tool in many countries to track the spread of the virus. Pharmaceutical companies, meanwhile, use R to calculate whether a new drug is effective and safe.

Three Decades of Dedication Recognised

At the heart of the R project, a core team has been working for some 30 years, responsible for the continued development and quality assurance of the base software. Martin Mächler, emeritus professor at the Seminar for Statistics at ETH Zurich, has been part of the team from the outset. Today, five members of the R core team have been awarded the Rousseeuw Prize for Statistics in recognition of their decades-long commitment and their foundational contributions to the success of the statistical programming language R.

Like the Nobel Prize, the Belgian Rousseeuw Prize carries a cash award of one million US dollars. It is presented every two years by the King Baudouin Foundation and funded by the statistician Peter Rousseeuw himself — an emeritus professor at KU Leuven, who began his academic career at ETH Zurich and later spent some time in the financial industry.

From Teaching Tool to Research Revolution

Half of the prize money — 500,000 US dollars — goes to the five open-source pioneers who have led the development of R. They are Martin Mächler, emeritus professor at ETH Zurich; Brian Ripley, professor at the University of Oxford; Kurt Hornik, professor at the Vienna University of Economics and Business; Peter Dalgaard, professor at Copenhagen Business School; and Luke Tierney, professor at the University of Iowa.

The remaining half of the prize money goes to the other members of the R core team, among them the two creators of R, Robert Gentleman and Ross Ihaka, who are explicitly honoured for the decisive impetus they provided. They developed R in the early 1990s for teaching and research at the University of Auckland.

They named their statistical language R partly as a nod to their own first names, and partly as a tribute to the older programming language S, developed in the 1970s and 1980s, on which R is built. S itself has served as a foundation for modern software such as Python, the programming language at the heart of machine learning and artificial intelligence. Accordingly, John Chambers, the creator of S, is also among the laureates.

Martin Mächler joined the R core team in the early 1990s. From 1991 he was a research associate at the Seminar for Statistics, becoming a professor there in 2020. In that role he was responsible for applied computational statistics and worked on the interface between data analysis and programming. He studied and completed his doctorate at ETH Zurich in statistics, at some interface of numerical analysis.

This branch of mathematics is concerned with solving problems as accurately and reliably as possible using computers — for instance by designing computational methods that are stable and minimise numerical errors. “At ETH Zurich I found my dream job,” says Mächler. “And early on, the statistics seminar had the vision that statistical computing and programming would be crucial to modern data science and statistical research.”

Software Quality as a Team Effort

Mächler has been able to put his expertise to good use within the R core team. Among his key contributions to the long-term success of R was ensuring high numerical accuracy of algorithms and more generally that the algorithms continued to function correctly and reliably after updates or extensions, and that they consistently produced dependable results. At the same time, he applied his knowledge to making the software transparent about emerging problems, so that users receive clear and helpful error messages. Mächler also played a significant role in making R the widely favoured tool it is today for data visualisation and graphics.

“What pleases me most is that the Rousseeuw Prize honours our team effort, thanks to which R has grown into the leading programming language for data analysis,” says Martin Mächler.

Peter Bühlmann, professor of mathematics at ETH Zurich since 1997 with a focus on computational statistics and Mächler’s long-standing line manager, adds that R has enabled enormous advances in research because R code could be published simultaneously with new methods: “This allowed researchers to apply and compare new methods immediately.” This, he says, has transformed research: “As the first free and open-source software for statistical computing, R has contributed enormously to the verification and reproducibility of scientific results.”

Open Source and the Core Team: The Keys to Success

One of Mächler’s most significant contributions was his commitment to keeping the development of R open. He made the case early on for the programming language to be released under a free licence — the GNU General Public License (GPL), which attracted collaboration with similarly minded Kurt Hornik in Vienna. This open-source model makes knowledge and tools freely accessible: the software can be used, modified, and redistributed at no cost. Because the source code is publicly available, it is also possible to see exactly how the programmes work — creating transparency and trust.

This organisational model has been central to the success of R. The core team is responsible for the continued development of the core software and ensures its stability. Extensions — known as packages — are developed by a large community. Before publication, each package undergoes a standardised process combining automated checks and human review to verify that it meets defined quality requirements. This distinction between centralised quality assurance of the foundations and open participation in their extension has contributed greatly to both the reach and the quality of R.

Lessons from a history of openness

For Martin Mächler, the history of R illustrates the strengths of independent open-source software: “The development of R teaches us that open source is at least as good as commercial software in terms of quality for data analysis and statistical algorithms. The fact that there are today specialised software extensions for almost every specialist field is only possible thanks to open source and the R network, which encompasses millions of users. No single company could deliver a project like R.”

Peter Bühlmann adds: “The R project is the most successful scientific software initiative in modern statistics and is firmly grounded in the principles of open access, open source, and reproducibility.” Bühlmann, who is also a member of the steering committee of the ETH AI Center, remarks — with an eye on the current open-source projects of ETH Zurich and EPFL in the field of artificial intelligence: “Open source is a very good strategy for universities, because it allows them to draw on a large number of distributed resources. At the same time, they can fulfil their responsibility in the independent assessment of new technologies and contribute to the open-source development and quality assurance of new, innovative technologies.”

The prize will be awarded on 4 November 2026 in Leuven in the presence of the Belgian King.

external page The Rousseeuw Prize for Statistics

external page The R Project for Statistical Computing

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17.06.2026 by Florian Meyer, Corporate Communications