The lab explores the complex dynamics of urban systems through advanced simulation, mobility analysis, and AI-driven spatial intelligence. We develop computational methods for understanding urban morphology, transportation networks, and metropolitan systems, with applications in smart city planning and real-time urban analytics.

Research Themes:

> Urban Complexity and Morphological Analysis: We apply complexity theory to decode urban growth patterns and spatial structures. Our research includes fractal analysis of Tel Aviv’s urban development, comparative studies of city morphologies across different economies, and scaling laws in metropolitan areas. We develop computational tools to analyze how cities self-organize and evolve, examining size distributions of urban entities and emergent spatial patterns.

> Transportation Networks and Mobility Intelligence: We create advanced network analysis methods for understanding transportation system topology and commuting patterns. Our MetroNet simulation platform models metropolitan commuting flows and predicts mobility scenarios. We analyze network resilience, accessibility patterns, and the relationship between transportation infrastructure and urban functionality across different economic contexts.

> AI-Driven Urban Analytics and Real-Time Systems: We develop machine learning frameworks for urban planning and real-time decision support. Our visualization tools, including The Flora system for personal network analysis, provide intuitive interfaces for exploring complex spatial data. We integrate diverse urban datasets (street networks, population density, building morphology) into interactive dashboards that enable planners to test interventions and optimize urban systems.

Selected Papers:

> Serok, N., Havlin, S., & Blumenfeld Lieberthal, E. (2022). Identification, cost evaluation, and prioritization of urban traffic congestions and their origin. Scientific reports, 12(1), 13026.

> Serok, N., Levy, O., Havlin, S., & Lieberthal, E. B. (2021). Studying the dynamics of urban traffic flows using percolation: a new methodology for real-time urban and transportation planning. In Handbook on Cities and Complexity (pp. 274-294). Edward Elgar Publishing.

> Serok, N., Levy, O., Havlin, S., & Blumenfeld-Lieberthal, E. (2019). Unveiling the inter-relations between the urban streets network and its dynamic traffic flows: Planning implication. Environment and planning b: urban analytics and city science, 46(7), 1362-1376.

> Duan, J., Zeng, G., Serok, N., Li, D., Lieberthal, E. B., Huang, H. J., & Havlin, S. (2023). Spatiotemporal dynamics of traffic bottlenecks yields an early signal of heavy congestions. Nature communications, 14(1), 8002.

> Lieberthal, E. B., Serok, N., Duan, J., Zeng, G., & Havlin, S. (2024). Addressing the urban congestion challenge based on traffic bottlenecks. Philosophical Transactions A, 382(2285), 20240095.

> Zeng, G., Serok, N., Lieberthal, E. B., Duan, J., Liu, S., Sui, S., … & Havlin, S. (2025). Unveiling city jam-prints of urban traffic based on jam patterns. Communications Physics, 8(1), 121.

For more information: efratbl@tauex.tau.ac.il