In the past few years, there has been much work on incorporating fairness requirements into
algorithmic rankers, with contributions coming from the data management, algorithms …

Participatory sensing is now becoming more popular and has shown its great potential in
various applications. It was originally proposed to recruit ordinary citizens to collect and …

Mobile crowdsourced sensing (MCS) is a new paradigm which takes advantage of
pervasive smartphones to efficiently collect data, enabling numerous novel applications. To …

Every day millions of crowdsourcing tasks are performed in exchange for payments. Despite
the important role pricing plays in crowdsourcing campaigns and the complexity of the …

A natural optimization model that formulates many online resource allocation problems is
the online linear programming (LP) problem in which the constraint matrix is revealed …

Off-the-shelf smartphones have boosted large scale participatory sensing applications as
they are equipped with various functional sensors, possess powerful computation and …

Mobile crowd sensing (MCS) is a new paradigm that takes advantage of pervasive mobile
devices to efficiently collect data, enabling numerous novel applications. To achieve good …

Machine learning (ML), and deep learning (DL) in particular, play a vital role in providing
smart services to the industry. These techniques, however, suffer from privacy and security …

Inspired by online ad allocation, we study online stochastic packing integer programs from
theoretical and practical standpoints. We first present a near-optimal online algorithm for a …

The need for responsible data management intensifies with the growing impact of data on
society. One central locus of the societal impact of data are Automated Decision Systems …