Gevorg Yeghikyan is an urban data scientist interested in studying cities with the mathematical apparatus of data science, machine learning, and complex systems, as well as understanding their relevance and impact on cities from an anthropological, historical, and sociological perspective. Gevorg holds a Ph.D. in data science from the Scuola Normale Superiore in Pisa and spent one year as a postdoctoral researcher at the Knowledge Discovery and Data Mining Lab (KDD Lab), a research group focusing on modeling urban mobility and socio-economic dynamics at the Italian National Research Council.
Higher education
2020, Ph.D. in Data Science
Scuola Normale Superiore of Pisa, Italy
2017, Master in Urban Planning
Frankfurt School of Applied Arts, Germany
2014, Bachelor of Urban Planning
National University of Architecture and Construction of Armenia
Courses taught:
- Spatial Data Science
- Urban Data Science
Publications:
Curado, M., Tortosa, L., Vicent, J.F. and Yeghikyan, G., 2021. Understanding mobility in Rome by means of a multiplex network with data. Journal of Computational Science, p.101305
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.
Yeghikyan, G., 2020, Class conflict in the age of AI: a changing urban landscape. Strelka Magazine.
Office location: 317W
Office hours: M/W 16:30 - 18:00