Research Seminar Series: Mehak Sachdeva

Lecture / Panel
For NYU Community

Mehak Sachdeva

NYU CUSP is pleased to host our annual Research Seminar Series, featuring leading voices in the growing field of urban informatics. The seminars will examine real-world challenges facing cities and urban environments around the world, with topics ranging from citizen and social sciences to smart infrastructure.

A Process-Driven Approach to Solving Long-Standing Problems in Geographical Analysis

A traditional aim of research in geographical sciences is to investigate the spatial pattern of a known phenomenon and to explain the underlying processes that contribute to the generation of that observed pattern.  This is often done through means of an a priori regression specification, through which the magnitude and direction of the conditioned associations affecting the spatial phenomenon are estimated enabling the spatial processes that generated the observed distribution to be inferred.   Local variants of this process-driven approach to geographical analysis can inform how social and behavioral processes generating spatial data vary over space, at what spatial scales those processes operate, and in turn predict the spatial patterns governed by these processes. However, the lens of local modeling can also provide a novel perspective through which we can discover knowledge about long-standing problems related to scale in geographical analysis, such as the Modifiable Areal Unit Problem (MAUP) and Simpson’s Paradox – problems, which until now have been studied almost exclusively from the perspective of data properties. This talk demonstrates these new insights and emphasizes the importance of a local process-driven approach to geographical analysis.

About the Speaker

Mehak Sachdeva is a faculty fellow at the Center for Urban Science and Progress at New York University. She was previously a postdoctoral research scholar at the Spatial Analysis Research Center at Arizona State University where she also graduated with a doctoral degree in Geographic Information Science in 2022. Her research involves developing local spatial statistical models to study the intangible social and behavioral processes and local associations driving socio-ecological interactions in urban and regional environments. Prior to pursuing academia, she has experience working at Carto, a web-mapping software company, and key government organizations such as the New York City Economic Development Cooperation and New York City Planning Department at Staten Island. She also has a graduate degree in urban and regional planning from Columbia University, and an undergraduate degree and professional background in architecture and landscape design from India. Apart from research, she is passionate about running, hiking, and painting.