TITLE: Quantifying biases in science ABSTRACT: Every day our life is made easier by efficient measures and algorithms that search and rank scientific information. Yet, these algorithms have an issue: they are trained on citations, which are ingrained with human biases. Therefore the output is inherently biased too, creating inequalities, raising concerns of discrimination, […]
Analysing cyclist behavior at signalized intersections using computer vision Artificial intelligence, in particular deep learning and computer vision, is a promising new tool for automated video analysis in traffic studies. It allows for facilitated extraction of detailed data from video recordings at higher efficiency and lower costs, improved precision of obtained data, and reduced errors […]
Network algorithms for the identification and classification of gaps in urban bicycle networks based on OSM data What is the best location to build new bicycle infrastructure in a city? This planning decision can be conceptualized as an optimization problem: the goal is to find the most efficient solution – that is, the one that […]
The geometric limits of growing urban bicycle networks City planners worldwide are increasingly realizing that cycling can be a promising solution to their unsustainable car-centric transport systems. However, common bicycle network planning practices follow piecewise ad hoc approaches which do not take into account the transportation network and its structural complexity as a whole. Here […]
Making cities better with human-centric urban data science Making our cities better and sustainable is key to solving the climate and urban transport crises. To this end, urban data science offers new tools to quantify societal problems in cities and to propose human-centric solutions to policy makers. In this talk I outline our recent and […]
Growing cohesive urban bicycle networks City planners worldwide are increasingly realizing that cycling can be a promising solution to their unsustainable car-centric transport systems. However, common bicycle network planning practices follow piecewise ad hoc approaches which do not take into account the transportation network and its structural complexity as a whole. Here we take a […]
Tom Brughmans, Aarhus University: Archaeological Network Research, illustrated through a study on visual signalling networks of Medieval strongholds in Garhwal Himalaya, India. This presentation provides a brief overview of network research in archaeology. What are the past phenomena typically studied using network methods in archaeology, and what empirical datasets tend to be represented as network data? When were these approaches adopted and how did the […]
Towards a human-centric urban data science Making our cities better and sustainable is key to solving the climate and urban transport crises. To this end, urban data science offers new tools to quantify societal problems in cities and to propose human-centric solutions to policy makers. In this talk I outline our recent and ongoing efforts […]
Understanding bikeability of urban networks Giulia Reggiani, Delft University of Technology About the author: Giulia Reggiani is ending her PhD in the department of Transport and Planning, Delft University of Technology. Her research in the last 4 years focused on structural properties of bicycle networks worldwide and on data driven methods for assessing bikeability. Her current […]
Abstract Social relationships are the key determinant of crucial societal outcomes, including diffusion of innovation, productivity, happiness, and life expectancy. To better attain such outcomes at scale, it is therefore paramount to have technologies that can effectively capture the type of social relationships from digital data. NLP researchers have tried to do so from conversational […]