World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9509
World Ranking
7497
National Ranking
3262

Mathematics

D-Index
44
Citations
9531
World Ranking
1565
National Ranking
675

Research.com Recognitions

  • 2018 - SIAM Fellow For fundamental and sustained contributions to the theory and practice of optimization, and for exemplary service to the optimization community.
  • 2016 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering
  • The Canadian Academy of Engineering

Overview

Tamás Terlaky is affiliated with Lehigh University in the United States. Their research spans several fields with a primary focus on Computer Science and Mathematics.

The scientist's main fields of study include:

  • Computer Science
  • Mathematics

Within these fields, the key subfields addressed are:

  • Artificial Intelligence
  • Numerical Analysis
  • Computational Theory and Mathematics
  • Civil and Structural Engineering
  • Electrical and Electronic Engineering

Tamás Terlaky's research topics cover a range of areas including:

  • Advanced Optimization Algorithms Research
  • Quantum Computing Algorithms and Architecture
  • Quantum Information and Cryptography
  • Advanced Multi-Objective Optimization Algorithms
  • Complexity and Algorithms in Graphs
  • Numerical Methods and Algorithms
  • Topology Optimization in Engineering

The scientist has contributed numerous papers, some notable recent examples include:

  • "An Inexact Feasible Quantum Interior Point Method for Linearly Constrained Quadratic Optimization" (2023), published in Entropy
  • "Truss topology design and sizing optimization with guaranteed kinematic stability" (2020), published in Structural and Multidisciplinary Optimization
  • "Characterization of QUBO reformulations for the maximum k-colorable subgraph problem" (2022), published in Quantum Information Processing
  • "Discrete multi-load truss sizing optimization: model analysis and computational experiments" (2021), published in Optimization and Engineering
  • "Efficient Use of Quantum Linear System Algorithms in Interior Point Methods for Linear Optimization" (2023), published in Preprints.org

Frequent publication venues for Tamás Terlaky include:

  • arXiv (Cornell University)
  • Optimization and Engineering
  • ACM Transactions on Quantum Computing
  • Mathematical Programming
  • EURO Journal on Computational Optimization

Several frequent co-authors have collaborated extensively with the scientist, among them:

  • Mohammadhossein Mohammadisiahroudi
  • Brandon Augustino
  • Ramin Fakhimi
  • Zeguan Wu
  • Luis F. Zuluaga

Recognition of their work includes several awards such as:

  • SIAM Fellow (2018) for contributions to optimization theory and practice, and service to the optimization community
  • Fellow of the Institute for Operations Research and the Management Sciences (INFORMS) (2016)
  • Membership in The Canadian Academy of Engineering

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

  • A Survey of the S-Lemma

    Imre Pólik;Tamás Terlaky

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

    Jiming Peng;Cornelis Roos;Tamás Terlaky

  • Interior Point Methods for Nonlinear Optimization

    Imre Pólik;Tamás Terlaky

  • 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

  • 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

  • Pivot rules for linear programming: A survey on recent theoretical developments

    Tamás Terlaky;Shuzhong Zhang

  • Sensitivity analysis in linear programming: just be careful!

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

  • A convergent criss-cross method

    T. Terlaky

  • Criss-cross methods: A fresh view on pivot algorithms

    Komei Fukuda;Tamás Terlaky

  • Optimal Nearly Analytic Discrete Approximation to the Scalar Wave Equation

    Dinghui Yang;Jiming Peng;Ming Lu;Tamas Terlaky

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

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

  • On Mehrotra-Type Predictor-Corrector Algorithms

    M. Salahi;J. Peng;T. Terlaky

  • The difference between the managerial and mathematical interpretation of sensitivity analysis results in linear programming

    Tamás Koltai;Tamás Terlaky

  • A NEW AND EFFICIENT LARGE-UPDATE INTERIOR-POINT METHOD FOR LINEAR OPTIMIZATION

    J. Peng;C. Roos;T. Terlaky

  • Pivot versus interior point methods: pros and cons

    Tibor Illés;Tamás Terlaky

  • Copositive realxation for genera quadratic programming

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

  • Optimization. Algorithms and consistent approximations: Elijah Polak Springer, New York, NY, 1997, ISBN 0-38794971-2, hb., 118 DM, 779 pages

    Tamás Terlaky

Frequent Co-Authors

Cornelis Roos
Cornelis Roos Delft University of Technology
Dick den Hertog
Dick den Hertog University of Amsterdam
Gerhard-Wilhelm Weber
Gerhard-Wilhelm Weber Poznań University of Technology
Shuzhong Zhang
Shuzhong Zhang University of Minnesota
Jean-Philippe Vial
Jean-Philippe Vial University of Geneva
Timothy J. Craig
Timothy J. Craig Pennsylvania State University
Immanuel M. Bomze
Immanuel M. Bomze University of Vienna
Peter A. Forsyth
Peter A. Forsyth University of Waterloo
Yinyu Ye
Yinyu Ye Stanford University
Jacek Gondzio
Jacek Gondzio University of Edinburgh

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