Urban Studies & 

Agent-Based Modeling


From Agent-Based Model to Digital Twins

Jan 2022-Urban digital twins can be created by utilizing the combination of ABM, synthetic population and other computational methods (e.g., machine learning).

Generation of Reusable Synthetic Population and Social Networks

July 2021Within agent-based models, agents interact with each other (e.g.,  social networks) and their environment, and it is through such interactions more aggregate patterns emerge (e.g., disease outbreaks, traffic jams). While the popularity of agent-based modeling has grown, one challenge remains, that of creating and sharing realistic synthetic populations which incorporate social networks. To overcome this challenge, this paper introduces a new approach that creates a reusable synthetic population using the New York Metro Area as a study area. Our method directly incorporates social networks (i.e., connections within a family or workplace) when creating a synthetic population. To demonstrate the utility and reusability of the synthetic population and to highlight the role of social networks, we show two example applications: traffic dynamics and the spread of a disease. These applications demonstrate how our synthetic population method can be easily utilized for different modeling problems.

Exploring Urban Shrinkage via computational Approaches 

May 2021- I have participated in the ACM SIGSIM PAD conference by introducing my research related to Urban Shrinkage. This presentation is part of my dissertation proposal and mainly focuses on three main questions: 1) To what extent can urban shrinkage be raveled by applying social media analysis (i.e., sentiment analysis)? 2) How urban shrinkage emerges at the macro-level through the simulation of housing trades at the individual level? 3) How can patterns of shrinkage be measured through social media analysis and simulation?