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About me
Researcher, builder, community member — AI for real-world impact.
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Posts
Spiegelmaschine
Published:
portfolio
CytoTransport
In-silico modeling of cellular transport mechanisms — bridging biomedicine, computational modeling, and structural biology.
OpenSKIZZE
An open-source AI assistant for climate-adapted urban planning — surrogate-assisted quality diversity optimization generates thousands of diverse design families, evaluated for cold airflow impact without costly CFD simulation.
UMMBAS — Molecular Modelling for Bio-Chemical Applications
Interdisciplinary initiative combining computational chemistry, machine learning, and immersive VR visualisation to decode biochemical systems.
Neue Stadtgärtnerei
A grassroots initiative in Bonn-Dransdorf creating climate-resilient space for affordable housing, agroforestry, and environmental education.
DT4MP — DigitalTwin-4-Multiphysics Lab
Research lab combining urban digital twins with industrial multi-physics simulation, powered by AI and machine learning.
KISS-BIS — AI for Elite Sports
Systematic research into the mismatch between AI/ML methods and elite sports practice, bridging Big Data methods with small-data sports science.
AErOmAt — Surrogate-Assisted Aerodynamic Optimisation
Metamodel-assisted exploration and optimisation of aerodynamic shapes — developing surrogate-illumination methods that won two best paper awards.
DoVE — Evolutionary Design of Aerodynamic Vehicle Bodies
Evolving 3D aerodynamic velomobile bodies using neural indirect encodings and real-world drag analysis via computer vision.
ELaBoR — EV Charging Infrastructure Optimisation
Evolutionary optimisation of electric vehicle charging station placement for the Bonn / Rhein-Sieg region.
STELLA — Efficient Mobility for Electric Velomobiles
Energy-optimal driving strategies and human-machine hybridisation for electrically assisted velomobiles.
Spiegelmaschine
A generative art project trained on 1000 paintings by artist Steffen Terk — producing infinite visual variations in the painter’s style.
publications
The b-it-bots Robo-Cup@ Home 2014 Team Description Paper
Published in Joao Pessoa, Brazil, 2014
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Recommended citation: 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.
The b-it-bots Robo-Cup at Home 2014 Team Description Paper
Published in Joao Pessoa, Brazil, 2014
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Recommended citation: Rhama Dwiputra, Matthias Füller, Frederik Hegger, Sven Schneider, Nico Hochgeschwender, Iman Awaad, Jos{\'e} Loza, Alexey Ozhigov, Saugata Biswas, Niranjan Deshpande, "The b-it-bots Robo-Cup at Home 2014 Team Description Paper." Joao Pessoa, Brazil, 2014.
How to successfully apply genetic algorithms in practice: Representation and parametrization
Published in In the proceedings of 2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA), 2015
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Recommended citation: 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.
Successive evolution of charging station placement
Published in In the proceedings of 2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA), 2015
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Recommended citation: 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.
Evolving parsimonious networks by mixing activation functions
Published in In the proceedings of Proceedings of the genetic and evolutionary computation conference, 2017
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Recommended citation: 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.
Hierarchical surrogate modeling for illumination algorithms
Published in In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2017
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Recommended citation: Alexander Hagg, "Hierarchical surrogate modeling for illumination algorithms." In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2017.
Multi-stage evolution of single-and multi-objective MCLP: Successive placement of charging stations
Published in Soft Computing, 2017
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Recommended citation: 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.
On recognizing transparent objects in domestic environments using fusion of multiple sensor modalities
Published in In the proceedings of RoboCup 2016: Robot World Cup XX 20, 2017
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Recommended citation: 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.
Prototype discovery using quality-diversity
Published in 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
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Recommended citation: 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.
Modeling user selection in quality diversity
Published in In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference, 2019
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Recommended citation: 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.
Prediction of neural network performance by phenotypic modeling
Published in In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2019
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Recommended citation: 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.
A Deep Dive Into Exploring the Preference Hypervolume
Published in In the proceedings of International Conference on Computational Creativity, 2020
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Recommended citation: 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.
AErOmAt Abschlussbericht
Published in In the proceedings of Hochschule Bonn-Rhein-Sieg, 2020
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Recommended citation: Alexander Asteroth, "AErOmAt Abschlussbericht." In the proceedings of Hochschule Bonn-Rhein-Sieg, 2020.
An analysis of phenotypic diversity in multi-solution optimization
Published in In the proceedings of International Conference on Bioinspired Methods and Their Applications, 2020
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Recommended citation: 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.
Designing air flow with surrogate-assisted phenotypic niching
Published in In the proceedings of International Conference on Parallel Problem Solving from Nature, 2020
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Recommended citation: 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.
Einsatz von Künstlicher Intelligenz im internationalen Spitzensport–Eine Erhebung des Status Quo
Published in spinfortec 2020 digital, 2020
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Recommended citation: Fabian Hammes, Daniel Link, Martin Lames, Alexander Hagg, Alexander Asteroth, Mark Pfeiffer, "Einsatz von Künstlicher Intelligenz im internationalen Spitzensport--Eine Erhebung des Status Quo." spinfortec 2020 digital, 2020.
Einsatz von K"unstlicher Intelligenz im internationalen Spitzensport–Eine Erhebung des Status Quo
Published in spinfortec 2020 digital, 2020
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Recommended citation: 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.
Einsatzmöglichkeiten und Transfer von Künstlicher Intelligenz im inter-nationalen Spitzensport–zwischen Small und Big Data
Published in spinfortec 2020 digital, 2020
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Recommended citation: Alexander Hagg, Alexander Asteroth, Mark Pfeiffer, Fabian Hammes, Daniel Link, "Einsatzmöglichkeiten und Transfer von Künstlicher Intelligenz im inter-nationalen Spitzensport--zwischen Small und Big Data." spinfortec 2020 digital, 2020.
Einsatzm"oglichkeiten und Transfer von K"unstlicher Intelligenz im inter-nationalen Spitzensport–zwischen Small und Big Data
Published in spinfortec 2020 digital, 2020
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Recommended citation: 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.
Discovering the preference hypervolume: an interactive model for real world computational co-creativity
Published in In the proceedings of Dissertation, 2021
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Recommended citation: Alexander Hagg, "Discovering the preference hypervolume: an interactive model for real world computational co-creativity." In the proceedings of Dissertation, 2021.
Expressivity of parameterized and data-driven representations in quality diversity search
Published in In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference, 2021
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Recommended citation: 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.
Phenotypic niching using quality diversity algorithms
Published in Metaheuristics for Finding Multiple Solutions, 2021
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Recommended citation: Alexander Hagg, "Phenotypic niching using quality diversity algorithms." Metaheuristics for Finding Multiple Solutions, 2021.
Artificial intelligence in elite sports—A narrative review of success stories and challenges
Published in Frontiers in Sports and Active Living, 2022
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Recommended citation: 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.
K"unstliche Intelligenz f"ur den Spitzensport im Spannungsfeld zwischen Big und Small Data
Published in In the proceedings of Hochschule Bonn-Rhein-Sieg, 2022
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Recommended citation: 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.
Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization
Published in Journal of chemical information and modeling, 2023
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Recommended citation: 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.
Efficient Quality Diversity Optimization of 3D Buildings through 2D Pre-optimization
Published in Evolutionary computation, 2023
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Recommended citation: 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.
On the Suitability of Representations for Quality Diversity Optimization of Shapes
Published in In the proceedings of Proceedings of the Genetic and Evolutionary Computation Conference, 2023
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Recommended citation: 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.
Open-source machine learning in computational chemistry
Published in Journal of chemical information and modeling, 2023
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Recommended citation: Alexander Hagg, Karl Kirschner, "Open-source machine learning in computational chemistry." Journal of chemical information and modeling, 2023.
Fine-tuning property domain weighting factors and the objective function in force-field parameter optimization
Published in Journal of Molecular Graphics and Modelling, 2025
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Recommended citation: Robin Strickstrock, Alexander Hagg, Marco Hülsmann, Karl Kirschner, Dirk Reith, "Fine-tuning property domain weighting factors and the objective function in force-field parameter optimization." Journal of Molecular Graphics and Modelling, 2025.
Full Domain Analysis in Fluid Dynamics
Published in Machine Learning and Knowledge Extraction, 2025
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Recommended citation: Alexander Hagg, Adam Gaier, Dominik Wilde, Alexander Asteroth, Holger Foysi, Dirk Reith, "Full Domain Analysis in Fluid Dynamics." Machine Learning and Knowledge Extraction, 2025.
Speed up Multi-Scale Force-Field Parameter Optimization by Substituting Molecular Dynamics Calculations with a Machine Learning Surrogate Model
Published in ChemPhysChem, 2025
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Recommended citation: Robin Strickstrock, Alexander Hagg, Dirk Reith, Karl Kirschner, "Speed up Multi-Scale Force-Field Parameter Optimization by Substituting Molecular Dynamics Calculations with a Machine Learning Surrogate Model." ChemPhysChem, 2025.
talks
How to successfully apply genetic algorithms in practice: Representation and parametrization
Published:
Quality Diversity Algorithms
Published:
Introduction to quality diversity algorithms and multi-solution optimization.
Artificial Intelligence in Social Work
Published:
Introductory lecture on artificial intelligence as applied (or applicable) to problems in social work for layman.
Workshop on AI: Large Language Models and Generative AI
Published:
Full-day workshop on large language models and generative AI for PhD and M.Sc. students. Covered foundational concepts, practical applications, and critical perspectives on current capabilities and limitations. Lecturer role.
Beyond Open Data and Towards Grass Roots Urban Ecology
Published:
Talk on moving beyond passive open data access towards community-driven, participatory approaches to urban ecology and climate adaptation. Explored how grassroots initiatives can generate and act on local environmental data.
Luftqualität und Klimawandel in der Stadtplanung – Wie künstliche Intelligenz uns hilft
Published:
Tandem talk on how AI methods — in particular surrogate models and generative tools — support urban planners in understanding and communicating the effects of climate change on local air quality. Part of the KLUGER Transfer initiative bridging research at H-BRS and the Max Planck Institute for Chemistry with policymakers and the public.
Innovationstreffen digitale Zwillinge für urbane Nachhaltigkeit
Published:
Impulse workshop on urban digital twins for sustainability. Brought together researchers, city administrations, and industry partners to explore how digital twin technology can support climate adaptation and sustainable urban development. Organised under the DT4MP Lab at H-BRS.
Workshop Digitaler Zwilling
Published:
Workshop on digital twin approaches for urban applications, presented for the City of Troisdorf. Covered methods for building operational digital twins of urban infrastructure and green spaces to support data-driven planning and climate adaptation.
AI as a programming and data analysis buddy (or how to start worrying and love the AI)
Published:
Practical talk on using AI tools as day-to-day coding and data analysis companions. Covered prompt engineering, code generation, and critical use of LLMs in scientific workflows — including where to trust them and where not to. Part of the KI-Wrap series at the H-BRS library.
teaching
Theoretical Computer Science
Undergraduate course, Bonn-Rhein-Sieg University of Applied Sciences, CS, 2011
This tutorial was given to students that had difficulties understanding the concepts of the theoretical computer science.
Algebra and Number Theory
Undergraduate course, Bonn-Rhein-Sieg University of Applied Sciences, CS, 2012
Exercise that accompanied the lecture series on abstract algebra and number theory.
Autonomous Mobile Robots
Graduate course, Bonn-Rhein-Sieg University of Applied Sciences, CS, 2013
For six semesters I was a teaching assistant, leading the exercises on programming for autonomous mobile robots. Using the Robot Operating System, Python and C++, students implemented algorithms for such tasks as path finding in a simulated environment. Coming from various backgrounds, the course also offered the possibility to learn programming from scratch. A high intensity course for first semester students, including individual and group work.
Genetic Algorithms & Neuroevolution
Undergraduate course, Bonn-Rhein-Sieg University of Applied Sciences, CS, 2015
For 10 semesters I gave courses on genetic algorithms and neuroevolution, including lectures and exercises and practical projects. Students implemented GAs, various genetic operators, and learned how to analyze results. In the neurevolution course, students learned how to evolve neural networks. Evolutionary techniques and neural networks were the two corner stones of these courses that I fully built and managed myself.
Evolutionary Computation, Theory and Application
Graduate course, Bonn-Rhein-Sieg University of Applied Sciences, CS, 2016
Master’s course on evolutionary computation, consisting of genetic algorithms, neuroevolution, genetic programming and the like. Heavily application oriented.