World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
7626
World Ranking
12425
National Ranking
205

Olaf Schenk publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Olaf Schenk sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 131 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Olaf Schenk D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Olaf Schenk sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2020 - ACM Senior Member
  • 2020 - SIAM Fellow For advances in the development of robust parallel sparse matrix algorithms and their effective use in large-scale science and engineering applications.

Overview

Olaf Schenk is affiliated with the Universita della Svizzera Italiana in Switzerland. Their research spans multiple aspects of computer science and engineering, with a particular focus on sparse matrix algorithms, Bayesian inference methods, and parallel computing techniques.

Their recent publications include:

  • A Recursive Algebraic Coloring Technique for Hardware-efficient Symmetric Sparse Matrix-vector Multiplication, 2020, ACM Transactions on Parallel Computing
  • New Frontiers in Bayesian Modeling Using the INLA Package in R, 2021, Journal of Statistical Software
  • Parallelized integrated nested Laplace approximations for fast Bayesian inference, 2022, Statistics and Computing
  • BELTISTOS: A robust interior point method for large-scale optimal power flow problems, 2022, Electric Power Systems Research
  • On cheap entropy-sparsified regression learning, 2022, Proceedings of the National Academy of Sciences

Their frequent co-authors include:

  • Juraj Kardoš
  • Matthias Bollhöfer
  • Håvard Rue
  • Lisa Gaedke-Merzhäuser
  • Dimosthenis Pasadakis

Olaf Schenk's work appears regularly in these publication venues:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Journal of Computational Science
  • Proceedings of the Annual Hawaii International Conference on System Sciences
  • ACM Transactions on Parallel Computing

Their primary fields of study are:

  • Computer Science
  • Engineering

Subfields of their research include:

  • Electrical and Electronic Engineering
  • Computational Mechanics
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications

Main research topics covered by Olaf Schenk are:

  • Sparse and Compressive Sensing Techniques
  • Statistical Methods and Bayesian Inference
  • Matrix Theory and Algorithms
  • Parallel Computing and Optimization Techniques
  • Distributed and Parallel Computing Systems
  • Gaussian Processes and Bayesian Inference
  • Probabilistic and Robust Engineering Design

Olaf Schenk has been recognized with the following awards:

  • SIAM Fellow, 2020, for advances in the development of robust parallel sparse matrix algorithms and their effective use in large-scale science and engineering applications
  • ACM Senior Member, 2020

Best Publications

  • Solving unsymmetric sparse systems of linear equations with PARDISO

    Olaf Schenk;Klaus Gärtner

  • ON FAST FACTORIZATION PIVOTING METHODS FOR SPARSE SYMMETRIC INDEFINITE SYSTEMS

    Olaf Schenk;Klaus Gärtner

  • On Large-Scale Diagonalization Techniques for the Anderson Model of Localization

    Olaf Schenk;Matthias Bollhöfer;Rudolf A. Römer

  • PATUS: A Code Generation and Autotuning Framework for Parallel Iterative Stencil Computations on Modern Microarchitectures

    Matthias Christen;Olaf Schenk;Helmar Burkhart

  • PARDISO: a high-performance serial and parallel sparse linear solver in semiconductor device simulation

    Olaf Schenk;Klaus Gärtner;Wolfgang Fichtner;Andreas Stricker

  • Matching-based preprocessing algorithms to the solution of saddle-point problems in large-scale nonconvex interior-point optimization

    Olaf Schenk;Andreas Wächter;Michael Hagemann

  • Efficient Sparse LU Factorization with Left-Right Looking Strategy on Shared Memory Multiprocessors

    O. Schenk;K. Gärtner;W. Fichtner

  • An Augmented Incomplete Factorization Approach for Computing the Schur Complement in Stochastic Optimization

    Cosmin G. Petra;Olaf Schenk;Miles C. Lubin;Klaus Gäertner

  • Fast methods for computing selected elements of the green's function in massively parallel nanoelectronic device simulations

    Andrey Kuzmin;Mathieu Luisier;Olaf Schenk

  • Toward the Next Generation of Multiperiod Optimal Power Flow Solvers

    Drosos Kourounis;Alexander Fuchs;Olaf Schenk

  • Real-Time Stochastic Optimization of Complex Energy Systems on High-Performance Computers

    Cosmin G. Petra;Olaf Schenk;Mihai Anitescu

  • Two-level dynamic scheduling in PARDISO: improved scalability on shared memory multiprocessing systems

    Olaf Schenk;Klaus Gärtner

  • A scalable hybrid linear solver based on combinatorial algorithms

    Madan Sathe;Olaf Schenk;Bora Uçar;Ahmed Sameh

  • Large-scale Sparse Inverse Covariance Matrix Estimation

    Matthias Bollhöfer;Aryan Eftekhari;Simon Scheidegger;Olaf Schenk

  • Algebraic Multilevel Preconditioner for the Helmholtz Equation in Heterogeneous Media

    Matthias Bollhöfer;Marcus J. Grote;Olaf Schenk

  • A Recursive Algebraic Coloring Technique for Hardware-Efficient Symmetric Sparse Matrix-Vector Multiplication

    Christie L. Alappat;Georg Hager;Olaf Schenk;Jonas Thies

  • State-of-The-Art Sparse Direct Solvers

    Matthias Bollhöfer;Olaf Schenk;Radim Janalik;Steve Hamm

  • Enhancing the scalability of selected inversion factorization algorithms in genomic prediction

    Fabio Verbosio;Arne De Coninck;Drosos Kourounis;Olaf Schenk

  • Optimal design of metal forming die surfaces with evolution strategies

    Olaf Schenk;Matthias Hillmann

  • Algorithmic performance studies on graphics processing units

    Olaf Schenk;Matthias Christen;Helmar Burkhart

Frequent Co-Authors

Gerhard Wellein
Gerhard Wellein University of Erlangen-Nuremberg
Lapo Boschi
Lapo Boschi University of Padua
Ahmed Sameh
Ahmed Sameh Purdue University West Lafayette
Dave A. May
Dave A. May University of Oxford
Gabriela Hug
Gabriela Hug ETH Zurich
Georg Hager
Georg Hager University of Erlangen-Nuremberg
Jeroen Tromp
Jeroen Tromp Princeton University
Dimitri Komatitsch
Dimitri Komatitsch Aix-Marseille University

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