World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
4385
World Ranking
10412
National Ranking
317

Overview

Markus Wagner is affiliated with Monash University in Australia. Their research spans multiple fields primarily within Computer Science and Engineering, with a strong focus on subfields including Artificial Intelligence, Information Systems, Computer Networks and Communications, Mechanical Engineering, and Industrial and Manufacturing Engineering.

The scientist's work covers a variety of topics, such as:

  • Metaheuristic Optimization Algorithms Research
  • Software Engineering Research
  • Evolutionary Algorithms and Applications
  • Software System Performance and Reliability
  • Advanced Multi-Objective Optimization Algorithms
  • Software Testing and Debugging Techniques
  • Wind Energy Research and Development

Frequent co-authors collaborating with Markus Wagner include:

  • Christoph Treude (22 publications)
  • Marcella Scoczynski Ribeiro Martins (11 publications)
  • Mehdi Neshat (9 publications)
  • Bradley Alexander (9 publications)
  • Bach Long Nguyen (8 publications)

Markus Wagner has published extensively, contributing to venues such as:

  • arXiv (Cornell University) with 42 publications
  • Proceedings of the Genetic and Evolutionary Computation Conference Companion with 10 publications
  • Empirical Software Engineering with 5 publications
  • Zenodo (CERN European Organization for Nuclear Research) with 5 publications
  • Procedia CIRP with 3 publications

Recent research articles authored or co-authored by Markus Wagner include:

  • "Wind turbine power output prediction using a new hybrid neuro-evolutionary method", 2021, published in Energy
  • "Benchmarking in Optimization: Best Practice and Open Issues", 2020, published in arXiv (Cornell University)
  • "Metaheuristics "In the Large"", 2021, published in European Journal of Operational Research
  • "Design procedure for triply periodic minimal surface based biomimetic scaffolds", 2021, published in Journal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials
  • "A hybrid cooperative co-evolution algorithm framework for optimising power take off and placements of wave energy converters", 2020, published in Information Sciences

Markus Wagner has also contributed to book publications, including a volume published by the European Organization for Nuclear Research in 2023 titled "ieee-cis/IEEE-CIS-Open-Access-Book-Volume-1: FirstEdition".

Best Publications

  • A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm

    Mehdi Neshat;Meysam Majidi Nezhad;Ehsan Abbasnejad;Seyedali Mirjalili

  • Evolutionary many-objective optimization: A quick-start guide

    Shelvin Chand;Markus Wagner

  • A comprehensive benchmark set and heuristics for the traveling thief problem

    Sergey Polyakovskiy;Mohammad Reza Bonyadi;Markus Wagner;Zbigniew Michalewicz

  • Node labeling schemes for dynamic XML documents reconsidered

    Theo Härder;Michael Haustein;Christian Mathis;Markus Wagner

  • A fast and effective local search algorithm for optimizing the placement of wind turbines

    Markus Wagner;Jareth Day;Frank Neumann

  • Development of underground mine monitoring and communication system integrated ZigBee and GIS

    Mohammad Ali Moridi;Youhei Kawamura;Mostafa Sharifzadeh;Emmanuel Knox Chanda

  • Wind turbine power output prediction using a new hybrid neuro-evolutionary method

    Mehdi Neshat;Meysam Majidi Nezhad;Ehsan Abbasnejad;Seyedali Mirjalili

  • Predicting the energy output of wind farms based on weather data: Important variables and their correlation

    Ekaterina Vladislavleva;Tobias Friedrich;Frank Neumann;Markus Wagner

  • A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

    Olaf Mersmann;Bernd Bischl;Heike Trautmann;Markus Wagner

  • Approximation-guided evolutionary multi-objective optimization

    Karl Bringmann;Tobias Friedrich;Frank Neumann;Markus Wagner

  • On the use of genetic programming to evolve priority rules for resource constrained project scheduling problems

    Shelvin Chand;Quang Nhat Huynh;Hemant K. Singh;Tapabrata Ray

  • A case study of algorithm selection for the traveling thief problem

    Markus Wagner;Marius Lindauer;Mustafa Mısır;Samadhi Nallaperuma

  • A fast approximation-guided evolutionary multi-objective algorithm

    Markus Wagner;Frank Neumann

  • Benchmarking in Optimization: Best Practice and Open Issues

    Thomas Bartz-Beielstein;Carola Doerr;Jakob Bossek;Sowmya Chandrasekaran

  • Metaheuristics “In the Large”

    Jerry Swan;Steven Adriaensen;Alexander E.I. Brownlee;Kevin Hammond

  • Faster black-box algorithms through higher arity operators

    Benjamin Doerr;Daniel Johannsen;Timo Kötzing;Per Kristian Lehre

  • Approximate Approaches to the Traveling Thief Problem

    Hayden Faulkner;Sergey Polyakovskiy;Tom Schultz;Markus Wagner

  • Performance analysis of ZigBee network topologies for underground space monitoring and communication systems

    Mohammad Ali Moridi;Youhei Kawamura;Mostafa Sharifzadeh;Emmanuel Knox Chanda

  • Escaping large deceptive basins of attraction with heavy-tailed mutation operators

    Tobias Friedrich;Francesco Quinzan;Markus Wagner

  • Optimizing the Layout of 1000 Wind Turbines

    Markus Wagner;Kalyan Veeramachaneni;Frank Neumann;Una-May O'Reilly

  • Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation

    Katya Vladislavleva;Tobias Friedrich;Frank Neumann;Markus Wagner

Frequent Co-Authors

Frank Neumann
Frank Neumann University of Adelaide
Tobias Friedrich
Tobias Friedrich Hasso Plattner Institute
Christoph Treude
Christoph Treude Singapore Management University
Yuval Yarom
Yuval Yarom Ruhr University Bochum
Lejla Batina
Lejla Batina Radboud University
Heike Trautmann
Heike Trautmann University of Münster
Zbigniew Michalewicz
Zbigniew Michalewicz University of Adelaide
Davide Astiaso Garcia
Davide Astiaso Garcia Sapienza University of Rome
Bernd Bischl
Bernd Bischl Ludwig-Maximilians-Universität München
Leandro L. Minku
Leandro L. Minku University of Birmingham

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

Exploring your educational options in Computer Science doesn't have to follow one path. There are a variety of flexible online learning choices designed to fit your career goals, time constraints, and budget.

For those looking to quickly boost their credentials, short certificate programs that pay well can help you gain in-demand skills and enter the workforce swiftly. Many students also pursue associates degrees online as a stepping stone into entry-level tech roles or as a foundation for further study.

If you're aiming to advance your career, completing one of the shortest online masters degree programs is a smart way to gain specialized knowledge without significant time away from work. Not all graduate programs are created equal, so it's wise to consider graduate degrees that are worth it for long-term job market value.

These online pathways offer flexibility, faster completion, and practical skills—helping you tailor your Computer Science education to your specific needs and career ambitions.

Best Scientists Citing Markus Wagner

Trending Scientists

Recently Published Articles