The Green Mobility City: Tools for Modeling Built Environments at the Pedestrian Scale Andres Sevtsuk Head, City Design and Development Group Associate Professor of Urban Science and Planning, Department of Urban Studies and Planning (DUSP)
The global climate-change crisis, along with public health and economic competitiveness challenges faced by cities worldwide, underscores the urgent need for analytical tools and models to explore the relationship between city design and sustainable mobility. In this presentation, Andres Sevtsuk will introduce the Urban Network Analysis framework, a tool for modeling land-use and transportation interactions at the pedestrian scale. This framework enables planners and policymakers to assess pedestrian access to urban destinations and evaluate the effects of land-use and infrastructure changes on pedestrian mobility. Such analyses empower planners, designers, and policymakers to prioritize projects that enhance sustainable mobility outcomes.
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What are the prospects for applying AI to improve healthcare? Three types of problems that AI can address in healthcare will be outlined, the most challenging of which is the development of new therapeutics. To address this challenge, we leverage recent advances in machine learning and high-throughput experimentation to apply the engineering cycle to drug discovery. The engineering cycle is based on iteratively measuring a system, modeling it computationally, and manipulating it. Each time the cycle is completed, the results improve. This iterative approach is fundamental to all engineering design but, until now, has had limited impact on drug discovery. Progress on unpublished projects relating to these efforts will be described, including a collaborative, multi-institutional project called Answer ALS.