Rhama Dwiputra, Matthias F{\"u}ller, Frederik Hegger, Sven Schneider, Nico Hochgeschwender, Iman Awaad, Jos{\'e} Loza, Alexey Ozhigov, Saugata Biswas, Niranjan Deshpande, "The b-it-bots Robo-Cup@ Home 2014 Team Description Paper." Joao Pessoa, Brazil, 2014.
Alexander Asteroth, Alexander Hagg, "How to successfully apply genetic algorithms in practice: Representation and parametrization." In the proceedings of 2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA), 2015.
Helge Spieker, Alexander Hagg, Alexander Asteroth, Stefanie Meilinger, Volker Jacobs, Alexander Oslislo, "Successive evolution of charging station placement." In the proceedings of 2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA), 2015.
Alexander Hagg, Maximilian Mensing, Alexander Asteroth, "Evolving parsimonious networks by mixing activation functions." In the proceedings of Proceedings of the genetic and evolutionary computation conference, 2017.
Alexander Hagg, "Hierarchical surrogate modeling for illumination algorithms." In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2017.
Helge Spieker, Alexander Hagg, Adam Gaier, Stefanie Meilinger, Alexander Asteroth, "Multi-stage evolution of single-and multi-objective MCLP: Successive placement of charging stations." Soft Computing, 2017.
Alexander Hagg, Frederik Hegger, Paul Pl{\"o}ger, "On recognizing transparent objects in domestic environments using fusion of multiple sensor modalities." In the proceedings of RoboCup 2016: Robot World Cup XX 20, 2017.
Alexander Hagg, Alexander Asteroth, Thomas B{\"a}ck, "Prototype discovery using quality-diversity." In the proceedings of Parallel Problem Solving from Nature--PPSN XV: 15th International Conference, Coimbra, Portugal, September 8--12, 2018, Proceedings, Part I 15, 2018.
Alexander Hagg, Alexander Asteroth, Thomas B{\"a}ck, "Modeling user selection in quality diversity." In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference, 2019.
Alexander Hagg, Martin Zaefferer, J{\"o}rg Stork, Adam Gaier, "Prediction of neural network performance by phenotypic modeling." In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019.
Alexander Hagg, Alexander Asteroth, Thomas B{\"a}ck, "A Deep Dive Into Exploring the Preference Hypervolume." In the proceedings of International Conference on Computational Creativity, 2020.
Alexander Asteroth, "AErOmAt Abschlussbericht." In the proceedings of Hochschule Bonn-Rhein-Sieg, 2020.
Alexander Hagg, Mike Preuss, Alexander Asteroth, Thomas B{\"a}ck, "An analysis of phenotypic diversity in multi-solution optimization." In the proceedings of International Conference on Bioinspired Methods and Their Applications, 2020.
Alexander Hagg, Dominik Wilde, Alexander Asteroth, Thomas B{\"a}ck, "Designing air flow with surrogate-assisted phenotypic niching." In the proceedings of International Conference on Parallel Problem Solving from Nature, 2020.
Fabian Hammes, Daniel Link, Martin Lames, Alexander Hagg, Alexander Asteroth, Mark Pfeiffer, "Einsatz von K"unstlicher Intelligenz im internationalen Spitzensport--Eine Erhebung des Status Quo." spinfortec 2020 digital, 2020.
Alexander Hagg, Alexander Asteroth, Mark Pfeiffer, Fabian Hammes, Daniel Link, "Einsatzm"oglichkeiten und Transfer von K"unstlicher Intelligenz im inter-nationalen Spitzensport--zwischen Small und Big Data." spinfortec 2020 digital, 2020.
Alexander Hagg, "Discovering the preference hypervolume: an interactive model for real world computational co-creativity." In the proceedings of Dissertation, 2021.
Alexander Hagg, Sebastian Berns, Alexander Asteroth, Simon Colton, Thomas B{\"a}ck, "Expressivity of parameterized and data-driven representations in quality diversity search." In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference, 2021.
Alexander Hagg, "Phenotypic niching using quality diversity algorithms." Metaheuristics for Finding Multiple Solutions, 2021.
Fabian Hammes, Alexander Hagg, Alexander Asteroth, Daniel Link, "Artificial intelligence in elite sports—A narrative review of success stories and challenges." Frontiers in Sports and Active Living, 2022.
Alexander Hagg, Alexander Asteroth, Christian Rasche, Kevin Bach, Mark Pfeiffer, "K"unstliche Intelligenz f"ur den Spitzensport im Spannungsfeld zwischen Big und Small Data." In the proceedings of Hochschule Bonn-Rhein-Sieg, 2022.
Max Müller, Alexander Hagg, Robin Strickstrock, Marco Hülsmann, Alexander Asteroth, Karl Kirschner, Dirk Reith, "Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization." Journal of chemical information and modeling, 2023.
Alexander Hagg, Martin Kliemank, Alexander Asteroth, Dominik Wilde, Mario Bedrunka, Holger Foysi, Dirk Reith, "Efficient Quality Diversity Optimization of 3D Buildings through 2D Pre-optimization." Evolutionary computation, 2023.
Ludovico Scarton, Alexander Hagg, "On the Suitability of Representations for Quality Diversity Optimization of Shapes." In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference, 2023.
Alexander Hagg, Karl Kirschner, "Open-source machine learning in computational chemistry." Journal of chemical information and modeling, 2023.
Robin Strickstrock, Alexander Hagg, Marco H{\"u}lsmann, Karl Kirschner, Dirk Reith, "Fine-Tuning Property Domain Weighting Factors and the Objective Function in Force Field Parameter Optimization." Arxiv, 2024.
Tutorial at International Symposium on Innovations in Intelligent SysTems and Applications, Madrid, Spain
Guest Lecture at LIACS lectures, Leiden, The Netherlands
Guest Lecture at IUBH lectures, IU, Düsseldorf/Cologne, Germany