World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
38
Citations
7092
World Ranking
2313
National Ranking
30

Engineering and Technology

D-Index
37
Citations
7009
World Ranking
8290
National Ranking
162

Overview

Cornelis Roos is affiliated with Delft University of Technology in the Netherlands. Their research spans several areas within mathematics and computer science, with a focus on optimization and combinatorial mathematics.

Their main fields of study include:

  • Mathematics
  • Computer Science

Within these fields, their work concentrates on various subfields such as:

  • Computational Theory and Mathematics
  • Numerical Analysis
  • Discrete Mathematics and Combinatorics
  • Management Science and Operations Research
  • Applied Mathematics

Cornelis Roos's research topics cover several advanced areas, including:

  • Advanced Optimization Algorithms Research
  • Advanced Combinatorial Mathematics
  • Risk and Portfolio Optimization
  • Advanced Multi-Objective Optimization Algorithms
  • Matrix Theory and Algorithms
  • Statistical and numerical algorithms
  • Mathematics and Applications

The scientist has contributed to scholarly literature with recent papers such as:

  • A Universal and Structured Way to Derive Dual Optimization Problem Formulations, 2020, INFORMS Journal on Optimization
  • Using Nemirovski's Mirror-Prox method as basic procedure in Chubanov's method for solving homogeneous feasibility problems, 2022, Optimization methods & software

Frequent co-authors collaborating with Cornelis Roos include:

  • Marleen Balvert
  • Bram L. Gorissen
  • Dick den Hertog
  • Yanqin Bai
  • Wei Zhang

In terms of publication venues, the researcher has published in:

  • INFORMS Journal on Optimization
  • Optimization methods & software

Best Publications

  • Theory and algorithms for linear optimization : an interior point approach

    C. Roos;T. Terlaky;J.-Ph. Vial

  • On implementing a primal-dual interior-point method for conic quadratic optimization

    Erling D. Andersen;Cornelis Roos;Tamás Terlaky

  • Self-Regularity: A New Paradigm for Primal-Dual Interior-Point Algorithms

    Jiming Peng;Cornelis Roos;Tamás Terlaky

  • A Comparative Study of Kernel Functions for Primal-Dual Interior-Point Algorithms in Linear Optimization

    Y. Q. Bai;M. El Ghami;C. Roos

  • Interior Point Methods for Linear Optimization

    Cornelis Roos;Tamás Terlaky;J. P Vial

  • Self-regular functions and new search directions for linear and semidefinite optimization

    Jiming Peng;Cornelis Roos;Tamás Terlaky

  • Robust Solutions of Uncertain Quadratic and Conic-Quadratic Problems

    A. Ben-Tal;A. Nemirovski;C. Roos

  • On Copositive Programming and Standard Quadratic Optimization Problems

    Immanuel M. Bomze;Mirjam Dür;Etienne De Klerk;Cornelis Roos

  • On maximization of quadratic form over intersection of ellipsoids with common center

    Arkadi Nemirovski;Cornelis Roos;Tamás Terlaky

  • Sensitivity analysis in linear programming: just be careful!

    B. Jansen;J.J. de Jong;C. Roos;T. Terlaky

  • A Full-Newton Step O ( n ) Infeasible Interior-Point Algorithm for Linear Optimization

    C. Roos

  • A New Efficient Large-Update Primal-Dual Interior-Point Method Based on a Finite Barrier

    Y. Q. Bai;M. El Ghami;C. Roos

  • A polynomial method of approximate centers for linear programming

    C. Roos;J.-Ph. Vial

  • On the Convergence of the Central Path in Semidefinite Optimization

    M. Halická;E. de Klerk;C. Roos

  • Cramer and Cayley-Hamilton in the max algebra

    G.J. Olsder;C. Roos

  • A new lower bound for the minimum distance of a cyclic code

    C. Roos

  • Initialization in semidefinite programming via a self-dual, skew-symmetric embedding

    E. de Klerk;C. Roos;T. Terlaky

  • A survey of search directions in interior point methods for linear programming

    D. den Hertog;C. Roos

  • Full Nesterov–Todd step infeasible interior-point method for symmetric optimization

    Guoyong Gu;Maryam Zangiabadi;Cornelis Roos

  • Copositive realxation for genera quadratic programming

    A.J. Quist;E. De klerk;C. Roos;T. Terlaky

Frequent Co-Authors

Tamás Terlaky
Tamás Terlaky Lehigh University
Dick den Hertog
Dick den Hertog University of Amsterdam
Arkadi Nemirovski
Arkadi Nemirovski Georgia Institute of Technology
Jean-Philippe Vial
Jean-Philippe Vial University of Geneva
Aharon Ben-Tal
Aharon Ben-Tal Technion – Israel Institute of Technology
Immanuel M. Bomze
Immanuel M. Bomze University of Vienna

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Pursuing a degree in Mathematics in the USA opens doors to diverse career paths and further educational opportunities, including various online programs designed for flexibility and accessibility. For those considering business-oriented roles, exploring options like what MBA programs can I get into can help identify programs with manageable admissions requirements.

If speed and convenience are priorities, many students benefit from researching the easiest and fastest online MBA programs, which can accelerate the transition into leadership positions without compromising learning quality.

For professionals seeking to advance their expertise further, affordable options like the most affordable online DBA programs provide doctoral-level education in business administration, ideal for those aiming at academic or executive careers.

Additionally, those interested in finance-related roles should consider the online masters in finance, which complements mathematical skills with financial acumen for various lucrative opportunities.

Exploring these related online degrees helps Mathematics graduates tailor their career pathways effectively while balancing affordability, speed, and program suitability.

Best Scientists Citing Cornelis Roos

Trending Scientists

Recently Published Articles