The 21st century would witness one of the largest urban migration in human history. A lot of research has gone into understanding the effects of the urban life on physical and mental health. The results have been unanimous: The urban environment has long lasting impacts on our well being. The facets of our urban environment that impact on our health and well being are called the urban exposome. In these projects, I attempt to quantify this exposome using techiques from deep learning, complex network, GIS, and NLP.
Can the shape of a city promote physical activity? The question of why individuals engage in physical activity has been widely researched, but that research has predominantly focused on socio-demographic characteristics (e.g., age, gender, economic …
Disruptions resulting from an epidemic might often appear to amount to chaos but, in reality, can be understood in a systematic way through the lens of “epidemic psychology”. According to Philip Strong, the founder of the sociological study of …
Since the uptake of social media, researchers have mined online discussions to track the outbreak and evolution of specific diseases or chronic conditions such as influenza or depression. To broaden the set of diseases under study, we developed a …
The presence of people in an urban area throughout the day -- often called 'urban vitality' -- is one of the qualities world-class cities aspire to the most, yet it is one of the hardest to achieve. Back in the 1970s, Jane Jacobs theorized urban …
I am very happy to announce the publication of “FaceLift: a transparent deep learning framework to beautify urban scenes” in the Royal soceity open science journal
Facelift is a Deeplearning driven algorithm, that goes beyond assessing beauty in urban scenes (streetviews) – as done by other studies in the field – and recreates the elements that can make any given urban scene more beautiful. It then explains away the elements behind the beauty using metrics which are commonly understood by the target users of this system such as Urban Planners and Architects.
In the area of computer vision, deep learning techniques haverecently been used to predict whether urban scenes are likely tobe considered beautiful: it turns out that these techniques areable to make accurate predictions. Yet they fall short when …
Information visualization has great potential to make sense of the increasing amount of data generated by complex machine-learning algorithms. We design a set of visualizations for a new deep-learning algorithm called FaceLift …