Computer scientist with a background in data science and statistics, specializing in agent-based modelling & simulation, experimental methodology, and policy analysis. Expert in developing evidence-based decision support…
Computer scientist with a background in data science and statistics, specializing in agent-based modelling & simulation, experimental methodology, and policy analysis. Expert in developing evidence-based decision support systems for complex social challenges with applications in public policy. Proficient in Python, GAMA, R, and NetLogo, with extensive experience in data science, network analysis, geographical information systems, and both agent-based and statistical modelling. Well-published researcher with a strong record of interdisciplinary collaboration, integrating political science and agent simulation to support real-world policy-making. Goal-oriented, continuous learner, who thrives in collaborative environments and is equally comfortable leading projects or contributing as part of a team.
Fully funded WASP-HS doctoral position within the project WASP-HS project: Realizing the Potential of Agent-Based Social Simulations applying design science research methodology to develop tools that facilitate the use of ABSS for evidence-based policymaking.
Regular presenter at leading international conferences, with 8+ peer-reviewed publications in venues including the Annual modelling and Simulation Conference (ANNSIM), the Multi-Agent-Based Simulation workshop (MABS), the Social Simulation Conference (SSC), and the Journal of Artificial Societies and Social Simulation (JASSS).
Active contributor to the research community through peer review, conference organization, and other scholarly service.
Successfully defended licentiate thesis (Jan 2025): Agent-based Social Simulation & Policy-Modelling: Facilitating Realistic and Credible Decision-Making Support.
Evaluates challenges and requirements for the responsible integration of ABSS as a decision-support tool in public institutions, focusing on quality-assurance frameworks for model verification, validation, and accreditation (VV&A).
Planned doctoral dissertation: From Simulation to Application: Agent-Based Social Simulation and AI Governance for Policy-Making.
Develop legal strategies and compliance tools to ensure ABSS models meet EU AI Act requirements for public-sector deployment.
Develop an operational ABSS model for disaster management and civil defense evacuation strategies in collaboration with Malmö City, serving as a proof-of-concept for the compliance framework.
Identified practical challenges and requirements for ABSS deployment in policy-making.
Designed model documentation protocols and VV&A frameworks.
Established institutional processes for credible simulation use.
Developed a legal strategy ensuring EU AI Act compliance.
Created agent-based models for policy experimentation with stakeholders.
Implemented GIS-integrated simulation systems to inform disaster management policy.
Fully funded WASP-HS doctoral position within the project WASP-HS project, Regular presenter at leading international conferences, Active contributor to the research community through peer review, conference organization, and other scholarly service, Successfully defended licentiate thesis (Jan 2025), Planned doctoral dissertation: From Simulation to Application: Agent-Based Social Simulation and AI Governance for Policy-Making, Identified practical challenges and requirements for ABSS deployment in policy-making, Developed a legal strategy ensuring EU AI Act compliance, Created agent-based models for policy experimentation with stakeholders, Implemented GIS-integrated simulation systems to inform disaster management policy
Research exchange as part of WASP-HS PhD programme, conducting collaborative research at the Laboratoire d’Informatique de Grenoble (LIG) on policy-modelling and agent-based social simulation for disaster management.
Strengthened international research networks.
Advanced technical expertise in GIS-integrated simulation systems and network analysis.
Contributed to cutting-edge research on agent–environment interaction and urban digital twins.
Contributed to ongoing collaborative publications in agent-based modelling and policy analysis.
Provided psychological and social rehabilitation support for youth under SoL and LVU legislation in a residential care setting.
Learned how to handle stressful situations.
Learned how to be there for people who struggle.
Became more empathetic and a better human being.
Designed and implemented complete data pipeline, Published findings demonstrating Statistics Sweden’s method for calculating the concentration of political appointments was systematically biased
Provided psychological and social rehabilitation support for youth under SoL and LVU legislation in a residential care setting
Technician for data science project analyzing political power concentration and institutional structures in Swedish municipalities using network analysis and computational methods.
Employed by Studieförbundet Näringsliv och Samhälle and Centre for Local Government Studies.
Designed and implemented complete data pipeline.
Performed web scraping using RegEx and pattern recognition.
Performed data cleaning and compilation.
Performed descriptive statistical analysis.
Constructed and visualized bipartite graphs.
Applied cluster and community detection algorithms.
Published findings (Wittberg et al. 2023) demonstrated Statistics Sweden’s (SCB) method for calculating the concentration of political appointments was systematically biased.
Research informed the 2022 Swedish Democracy Report.
Conducted collaborative research at the Laboratoire d’Informatique de Grenoble (LIG) on policy-modelling and agent-based social simulation for disaster management, Contributed to cutting-edge research on agent–environment interaction and urban digital twins
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