Alexander Hagg

Dr. Alexander Hagg is a Researcher at Hochschule Bonn-Rhein-Sieg (H-BRS) in the Department of Engineering and Communication, affiliated with the Institute of Technology, Resource Conservation and Energy Efficiency (TREE). With a PhD from Leiden University, he specializes in evolutionary computation, machine learning, and computer-aided ideation, focusing on applications in climate adaptation, energy efficiency, and resource conservation. His work bridges theoretical research with practical applications across multiple domains including urban planning, computational chemistry, and robotics.

• PhD in Computer Aided Ideation (2017-2020) - Leiden University
• Master's in Autonomous Systems (2013-2016) - Bonn-Rhein-Sieg University of Applied Sciences
• Bachelor's in Computer Science (2009-2013) - Bonn-Rhein-Sieg University of Applied Sciences

Dr. Hagg's research centers on efficient computer-aided ideation algorithms that help understand early on what good solutions to complex problems might look like. His primary focus is on quality diversity algorithms, which efficiently create diverse sets of high-performing solutions to inform engineers' intuition. His work spans multiple application domains including urban climate resilience, structural chemistry, robotics, and digital twins for urban planning. He is particularly interested in how AI can serve as a co-designer, helping humans explore and understand complex optimization and data domains.

His recent publications reveal a strong trend toward applying evolutionary computation and machine learning to real-world engineering problems. A significant portion of his work focuses on computational chemistry and force-field parameter optimization, where machine learning substitutes expensive molecular dynamics calculations. Another major theme involves quality diversity algorithms applied to urban planning and building design. His research consistently emphasizes practical applications in climate adaptation and resource efficiency, with growing interest in digital twins for urban sustainability.

• 2023: GECCO Best Paper Award (honourable mention)
• 2022: ACM SIGEVO Best Dissertation Award (honourable mention)
• 2017: AFCEA Studienpreis
• 2017: GECCO Best Student Paper Award (honourable mention)
• 2016: RoboCup Symposium Best Paper Award

Dr. Hagg has led multiple research projects including OpenSKIZZE (open-source tools for climate-adaptive urban development), Digital Twin-4-Multiphysics Lab (DT4MP), and KISs-BiS (AI for elite sports). He teaches courses on evolutionary computation, AI, and machine learning, and has developed workshops on digital twins for urban sustainability. His research is supported by collaborations with institutions including University of Siegen, University College London, University of Leiden, and various Fraunhofer institutes.

He leads the Digital Twin-4-Multiphysics Lab (DT4MP) which focuses on urban digital twins and multiphysics twins for industry. Dr. Hagg is also active in several research groups including the Computational Chemistry Working Group at H-BRS and serves as a representative for H-BRS in the GeoIT Round Table NRW. His work often involves interdisciplinary teams spanning computer science, engineering, urban planning, and environmental science.