World's Best Scientists 2026 revealed!
Sara van de Geer

Sara van de Geer

D-Index & Metrics

Mathematics

D-Index
43
Citations
20230
World Ranking
1640
National Ranking
32

Sara van de Geer publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Sara van de Geer sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

This scientist: 176 publications — 52nd percentile

52% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 537 publications or more.

Sara van de Geer D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Sara van de Geer sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

This scientist: 43 D-Index — 54th percentile

54% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 86 D-Index or more.

Research.com Recognitions

  • 2020 - Member of Academia Europaea
  • 2016 - Wald Memorial Lecturer

Overview

Sara van de Geer is affiliated with ETH Zurich in Switzerland, contributing extensively to the fields of mathematics, computer science, and engineering. Their work spans multiple subfields such as statistics and probability, computational mechanics, artificial intelligence, and computational mathematics.

Their research primarily addresses topics including statistical methods and inference, sparse and compressive sensing techniques, machine learning and algorithms, probabilistic and robust engineering design, tensor decomposition and applications, mathematical approximation and integration, and neural networks and applications.

Frequent coauthors in their research collaborations include Geoffrey Chinot, Matthias Löffler, Felix Kuchelmeister, Francesco Ortelli, and Peter Hinz.

Publications by Sara van de Geer have appeared across a range of venues. These include:

  • arXiv (Cornell University)
  • The Annals of Statistics
  • Mathematical Statistics and Learning
  • Oberwolfach Reports
  • SIAM/ASA Journal on Uncertainty Quantification

Recent papers from their research portfolio are:

  • Convergence Rates for Penalized Least Squares Estimators in PDE Constrained Regression Problems, 2020, SIAM/ASA Journal on Uncertainty Quantification
  • De-Biased Sparse PCA: Inference for Eigenstructure of Large Covariance Matrices, 2021, IEEE Transactions on Information Theory
  • Prediction bounds for higher order total variation regularized least squares, 2021, The Annals of Statistics
  • On the robustness of minimum norm interpolators and regularized empirical risk minimizers, 2022, The Annals of Statistics
  • AdaBoost and robust one-bit compressed sensing, 2022, Mathematical Statistics and Learning

Sara van de Geer is recognized as a member of Academia Europaea since 2020 and was the Wald Memorial Lecturer in 2016.

Best Publications

  • Statistics for High-Dimensional Data: Methods, Theory and Applications

    Peter Bhlmann;Sara van de Geer

  • The group lasso for logistic regression

    Lukas Meier;Sara Van De Geer;Peter Bühlmann

  • On asymptotically optimal confidence regions and tests for high-dimensional models

    Sara van de Geer;Peter Bühlmann;Ya’acov Ritov;Ruben Dezeure

  • A global test for groups of genes: testing association with a clinical outcome

    Jelle J. Goeman;Sara A. Van De Geer;Floor De Kort;Hans C. Van Houwelingen

  • Empirical Processes in M-Estimation

    Sara A. van de Geer

  • High-dimensional generalized linear models and the lasso

    Sara A. van de Geer

  • On the conditions used to prove oracle results for the Lasso

    Sara A. van de Geer;Peter Bühlmann

  • High-dimensional additive modeling

    Lukas Meier;Sara van de Geer;Peter Bühlmann

  • Oracle Inequalities and Optimal Inference under Group Sparsity

    Karim Lounici;Massimiliano Pontil;Sara van de Geer;Alexandre B. Tsybakov

  • Locally adaptive regression splines

    Enno Mammen;Sara van de Geer

  • ℓ1-penalization for mixture regression models

    Nicolas Städler;Peter Bühlmann;Sara van de Geer

  • Regularization in Statistics

    Peter J. Bickel;Bo Li;Alexandre B. Tsybakov;Sara A. van de Geer

  • Testing against a high dimensional alternative

    Jelle J. Goeman;Sara A. Van De Geer;Hans C. Van Houwelingen

  • Ecole d'été de probabilités de Saint-Flour XLV

    Sara van de Geer

  • Taking Advantage of Sparsity in Multi-Task Learning

    Karim Lounici;Massimiliano Pontil;Alexandre B. Tsybakov;Sara A. van de Geer

  • Hellinger-Consistency of Certain Nonparametric Maximum Likelihood Estimators

    Sara van de Geer

  • Correlated variables in regression: Clustering and sparse estimation

    Peter Bühlmann;Philipp Rütimann;Sara van de Geer;Cun-Hui Zhang

  • Estimating a Regression Function

    Sara van de Geer

  • Estimation for High‐Dimensional Linear Mixed‐Effects Models Using ℓ1‐Penalization

    Jürg Schelldorfer;Peter Bühlmann;Sara Van De Geer

  • Confidence intervals for high-dimensional inverse covariance estimation

    Jana Janková;Sara van de Geer

  • Penalized quasi-likelihood estimation in partial linear models

    Enno Mammen;Sara van de Geer

Frequent Co-Authors

Alexandre B. Tsybakov
Alexandre B. Tsybakov École Nationale de la Statistique et de l'Administration Économique
Jon A. Wellner
Jon A. Wellner University of Washington
Enno Mammen
Enno Mammen Heidelberg University
Vladimir Koltchinskii
Vladimir Koltchinskii Georgia Institute of Technology
Massimiliano Pontil
Massimiliano Pontil Italian Institute of Technology
Arie Kapteyn
Arie Kapteyn University of Southern California
Bin Yu
Bin Yu University of California, Berkeley
Leen Stougie
Leen Stougie Centrum Wiskunde & Informatica

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Choosing the right degree depends on career goals, time commitment, and financial considerations. These diverse online pathways highlight how mathematics graduates can leverage their skills across multiple high-demand sectors.

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