AI-supported economic research for resilience, sustainability, and policy design. Bridging dynamic economics, complex systems, and artificial intelligence for real-world decision-making.
SEDAI is dedicated to advancing sustainability, welfare, and resilience in economies confronting the defining challenges of our era—climate change, external shocks, rapid technological transformation, and widening distributional disparities.
Operating at the nexus of dynamic economic theory, complex systems analysis, and artificial intelligence, the Center translates rigorous analysis into practical, policy-relevant tools for reshaping innovation pathways, improving market outcomes, and reducing climate-related risks.
Nonlinear macro-finance, business cycle dynamics, and structural change
Multi-regime models, feedback loops, and tipping-point analysis
MPC, ML, RL, and AMPL for estimation, control & forecasting
Deployable instruments for evidence-based economic governance
The Center pursues complementary objectives that together form a comprehensive program for AI-supported economic research.
Examining how AI-supported technologies shape output, productivity, innovation, labor market transitions, financial dynamics, healthcare, income and wealth inequality, and climate performance.
Integrating MPC, ML, RL, and AMPL into forecasting, regime-change detection, scenario evaluation, multi-period Nash games, risk management, and policy optimization—particularly in nonlinear, heterogeneous settings.
Overcoming the persistent disconnect between AI engineering, short-term financial decision-making, and long-horizon policy design.
Modern computational methods—machine learning, reinforcement learning, and control theory—brought to bear on economic questions with causal interpretability.
Overcoming costly short-termism in economic and financial decisions through finite-horizon frameworks and multi-phase optimization.
Intertemporal, multi-goal policy frameworks combining the discipline of economic structure with the adaptability of contemporary AI tools.
Development of AI/ML, Model Predictive Control, and AMPL methodologies to enhance macroeconomic modeling, forecasting, and policy simulation—specifically regarding nonlinear dynamics and real-time decision-making in complex environments.
Empirical analysis of AI adoption and its effects on labor markets, financial markets, the environment, innovation, productivity, wage distributions, inflation, and industry and firm-level competition across advanced economies.
The Center's establishment in Europe is driven by specific analytical and regulatory requirements of the region.
Exploring economically relevant policies, emerging trends, and business cycle phases across the European region.
Leveraging AI adoption to explore economic innovation dynamics, ecological transition, and labor market impacts.
Generating causal evidence on AI-driven inequality, employment volatility, labor shifts, and demographic transitions.
Building on Europe's regulatory framework for responsible, evidence-based AI deployment addressing vulnerable populations and skill shifts.
Integrated research programs producing technical papers, open-source toolkits, dashboards, and policy-grade frameworks.
Co-production with institutional partners ensuring technical alignment and deployment viability across macroeconomic, sectoral, and industry policy domains.
Comprehensive evaluation of policy effects across economic sectors and populations
Sectoral change analysis for expansion, contraction, and inflationary effects of decarbonization
AI-supported macro and sectoral stress testing for resilience and scenario planning
Macroeconomic and sector-level instruments for climate, labor, and financial policy
The Center is led by researchers with deep expertise in macroeconomic dynamics, financial instability, climate economics, and computational policy design.
Professor Emeritus, The New School for Social Research and Bielefeld University. Research spans macro-financial dynamics, industrial competition, climate economics, and computational policy design.
Researcher in macroeconomic dynamics and AI-supported policy analysis, contributing to the Center's integrated modeling and applied research program.
Ph.D., Senior Lecturer at Curtin University, Australia. Specialist in complex systems empirics and econometric validation through time series and panel methods.
Maintaining visibility and impact through publications, convenings, and a broad international network of collaborating institutions.
Peer-reviewed publications, technical policy briefs, standardized open datasets and codebases.
Publications on Economic Dynamics and AI; comprehensive annual research reports.
Flagship conferences, workshops, technical seminars, and specialized training for researchers and policymakers.
Lars Grüne (Bayreuth), Helmut Maurer (Münster), Giovanni di Bartolomeo (La Sapienza), Stefan Mittnik (LMU), Timo Teräsvirta (Aarhus)
To be confirmedT. Khundadze, P. Chen, F. Koohi-Kamali, T. Bonen, E. Ernst, L. Mateane, S. Issa, C. Proaño, B. Fard, J. Bastos Neves, O. Valle Codina, B. Lucas, U. Nyambuu, M. Toure
To be confirmedIIASA, City University NY, Bamberg University, FMND (Paris/Lille), Milano group, VAW, MPI, Geneva Lab, La Sapienza, Bielefeld University, Oxford University, UCL
To be confirmedBringing together researchers, practitioners, and policymakers through high-impact events and training programs.
The Center's flagship convening, gathering leading researchers and policymakers to present cutting-edge work in AI-supported economics.
Hands-on workshops with institutional partners focused on deploying AI-supported tools for sectoral analysis and policy evaluation.
Advanced technical seminars for PhD-level researchers on nonlinear modeling, MPC, reinforcement learning, and structural estimation.
We welcome collaboration from researchers, policymakers, institutions, and partners who share our commitment to rigorous, AI-supported economic research for a more resilient and equitable future.