I’m a PhD in spatial data science and an urban planner, studying cities with machine learning, spatial statistics, and complex networks techniques at the KDD Lab in Pisa, Italy. Here I share my work, ideas, insights, replications of peer papers, as well as discussions about urban data science, smart cities, data-driven urban planning, operations research, urban economics, and how cities actually work.

Working with urban planning firms, municipalities, UNDP, GIZ, and the World Bank, I also consult urban development, master planning, (E-) mobility, and transportation projects worldwide.

You can find my CV here. Do not hesitate to contact me for questions, suggestions, and collaborations.


  • Curado, M., Tortosa, L., Vicent, J.F. and Yeghikyan, G., 2020. Analysis and comparison of centrality measures applied to urban networks with data. Journal of Computational Science, p.101127.
  • Yeghikyan, G., Opolka, F.L., Nanni, M., Lepri, B. and Lio, P., 2020. Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks. arXiv preprint arXiv:2004.11924.
  • Yeghikyan, G., Nanni, M., Tortosa, L., and Vicent, J.F., 2020, Ranking places in attributed temporal urban mobility networks. PLoS One, 15 (10), e0239319
  • M., Tortosa, L., Vicent, J.F. and Yeghikyan, G., 2020, An algorithm for ranking the nodes of multiplex networks with data based on the PageRank concept. Applied Mathematics and Computation, 392, 125676 (Can be accessed here)
  • You can watch my PhD defence here. A draft of my PhD thesis titled “Urban Structure and Mobility as Spatio-temporal complex Networks” can be found here, the slides of a short presentation here.