The lack of information regarding cycling safety prompts local governments and bicycle associations to look into ways of making cycling in urban areas both more attractive and safer. Using data mining and machine learning techniques, this project can measure bicycle safety from citizens’ complaints and concerns.
I'm interested in social computing with a focus on the intersection between big data, policy and social development. I combine data mining and applied machine learning techniques to extract socially significant information from digital traces of mobile and ubiquitous technologies. My ultimate goal is to reveal behavioral fingerprints that might be useful to organizations and policy makers working for social development.
PhD, Columbia University
Big data analytics, machine learning, mobile and ubiquitous technologies, behavior and user modeling, crowdsourcing, ICTs for development