Rate My Professor Markus Wagner

Monash University

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5.05/4/2026

A true role model for academic success.

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About Markus

Markus Wagner is an Associate Professor in the Department of Data Science and AI, Faculty of Information Technology, at Monash University, Australia, and Deputy Director (Research) of the Monash AI Institute. He completed his PhD in Computer Science at the University of Adelaide in 2013, with a thesis titled "Theory and Applications of Bio-Inspired Algorithms," for which he received the 1st University Doctoral Research Medal. Earlier, he earned a Diplom in Computer Science, specializing in Artificial Intelligence and Theoretical Computer Science, from the University of Koblenz and Landau in 2009. His doctoral studies were conducted at both the Max Planck Institute for Informatics in Saarbrücken, Germany, and the University of Adelaide.

Wagner's academic career at the University of Adelaide spanned from Lecturer (2013-2016) to Senior Lecturer (2017-2020), Associate Professor (2021-2022), and Acting Head of the School of Computer Science and Mathematical Sciences (February to July 2022). Since 2023, he has held his current position at Monash University while maintaining an adjunct associate professor role at Adelaide. His research encompasses mathematical runtime analysis of heuristic optimisation algorithms, theory-guided algorithm design, search-based software engineering, and applications in renewable energy production such as wind and wave farms. He has authored approximately 200 articles with about 250 co-authors, accumulating over 5,000 citations and an h-index exceeding 40. Wagner has secured over AUD 14 million in funding, including AUD 3 million as lead investigator, from partners like Google, Facebook, and companies in defence, mining, sports, and energy. His achievements include the ARC Discovery Early Career Researcher Award (2016-2018), four best paper awards, one HUMIES Gold Award, the 2024 Biannual German IT Security Award, one best presentation award, and one medal. Select publications are "Cumulative Step Size Adaptation for Adaptive SEMO in Integer Space" (2025), "Future schools and the energy implications of AI in education: A review of scenarios and method for engaging young people in futures thinking" (2025, Policy Futures in Education), "Information-theoretic detection of unusual source code changes" (2025, Empirical Software Engineering), and "A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters" (2019, GECCO Best Paper Award). He served as General Chair of GECCO 2022, Treasurer of the ACM Special Interest Group on Genetic and Evolutionary Computation, founder of the IEEE CIS Task Force on Computational Intelligence in the Energy Domain and IEEE CIS Task Force on Benchmarking, Senior Advisor to the Monash Energy Institute, and co-founder of Data-Driven Search-Based Software Engineering.