Seminars

As part of the IHE-Lead program, we run a monthly seminar series that is open to the GT public. Speakers across GT colleges will talk about their research at the interface of human and environmental health, and discuss opportunities and challenges for translating scholarly work into actions with public impact and visibility. Our seminar series provides an opportunity for trainees and experts across GT colleges to exchange ideas and create new connections to work toward a shared goal of improving human and environmental health.

Missed a talk? You can access recordings of past seminars here (requires GT login).

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Clio Andris is an associate professor holding a joint appointment at the College of Design and College of Computing (School of City and Regional Planning and the School of Interactive Computing) at Georgia Tech. Her research focuses on mathematical models of social networks, social flows, and interpersonal relationships in geographic space, applied to issues of urban planning, visualization, transportation and geography.

Seminar details: The talk begins at 10:30am on Wednesday, January 25th 2023, in IBB, room 1128. Coffee and snacks will be provided starting at 10am.

Abstract:

In this interactive talk, I will describe some GIS paradigms inherent to mapping people, administrative boundaries, and the physical environment. We will present a few creative problem solving / how-to exercises and work together in pairs / small groups to generate approaches to best model a spatial phenomenon. These exercises will include issues such as spatial data interpolation, capturing population in an area, measuring edge effects, raster (grid cell) combination, creating indexes, and gerrymandering. With each, I will comment on our collective answers vis-a-vis some best practices used in the GIS community.  Participants are expected to interact and work with others to think through these modeling techniques. The overall goal is to show how input data and choices can affect results of spatial data analyses, and that there are many different ways to model the same data.