Martin Maechler
Martin Maechler is a Swiss computational statistician and a professor emeritus at ETH Zurich. He has worked as a co-developer of R, a widely used environment for statistical computing and graphics, and is a long-time member of the R Core Development Team.
Education and career
Maechler pursued his academic studies at ETH Zurich, earning a Ph.D. in mathematics in 1989 focusing on nonparametric regression and curve estimation. His doctoral advisors were Frank Hampel and Hans-Rudolf Künsch. He conducted post-doctoral research at the University of Washington's Department of Statistics from August 1989 to August 1990.He has dedicated most of his professional career to ETH Zurich's Seminar for Statistics, serving as a Senior Scientist and Lecturer before becoming a professor emeritus. His primary areas of research and teaching include computational statistics, robust statistical methods, clustering algorithms, and numerical computations, particularly with matrices.
R Project involvement
Maechler is considered a pioneer in the development of the R programming language. He joined the R Project in 1995 shortly after its inception, drawn by the open-source nature of the environment. His motivation was to "create something meaningful for mankind," particularly aiding universities in poorer countries that benefit from the open-source model.He is a member of the R Core Development Team and serves as the Secretary General of the R Foundation. Maechler has authored/maintained numerous R packages, including:
Matrix: for sparse and dense matrix classes.cluster: provides methods for cluster analysis.robustbase: offering fundamental robust statistical methods.Maechler is also a key figure in the development of Emacs Speaks Statistics, an add-on for the GNU Emacs text editor that provides dedicated support for statistical programming languages like R. He has been an ESS Core Developer since around 1997 and served as the project leader since 2004.
Selected publications
Maechler has co-authored publications and R packages in the domain of linear and generalized linear mixed-effects models. One of his highly cited works is the R packagelme4. He has also contributed to the field of data visualization with the scatterplot3d package.