Urban life has been increasingly grounded in mobilities as technological advances induce faster, cheaper, and more seamless mobility options. However, people’s experiences of such advances are shaped by their race, gender, class, other socially constructed dimensions, and the intersections of these dimensions. Despite the growing popularity of intersectionality lens, quantitative methods often fall short in testing intersectional hypotheses. Difficulty in quantitative studies comes from the non-additive and high-dimensional nature of intersectionality. This presentation will introduce Dr. Zhong’s current research on using interpretable machine learning approaches to develop a better understanding of the intersectionality of emerging mobilities.
Speaker: Dr. Haotian Zhong
Dr. Haotian Zhong is an Assistant Professor in the School of Public Administration and Policy at Renmin University of China. His recent efforts in teaching and research focus on centering justice and equity in all discussions of emerging technologies. He serves as an associate editor for the Journal of Transport and Land Use.
