World's Best Scientists 2026 revealed!

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Computer Science

D-Index
33
Citations
7626
World Ranking
12427
National Ranking
205

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
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
Yousef Saad
Yousef Saad University of Minnesota

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