10 citations · 16 across the 8 of their papers we have counts for
6 papers · 1 filter
Generative Models for Simulating Mobility Trajectories
Vaibhav Kulkarni, Natasa Tagasovska, Thibault Vatter +1
Mobility datasets are fundamental for evaluating algorithms pertaining to geographic information systems and facilitating experimental reproducibility. But privacy implications res…
On the Inability of Markov Models to Capture Criticality in Human Mobility
Vaibhav Kulkarni, Abhijit Mahalunkar, Benoit Garbinato +1
We examine the non-Markovian nature of human mobility by exposing the inability of Markov models to capture criticality in human mobility. In particular, the assumed Markovian natu…
Addressing the Free-Rider Problem in Public Transport Systems
Vaibhav Kulkarni, Bertil Chapuis, Benoît Garbinato +1
Public transport network constitutes for an indispensable part of a city by providing mobility services to the general masses. To improve ease of access and reduce infrastructural…
Geodabs: Trajectory Indexing Meets Fingerprinting at Scale
Bertil Chapuis, Benoit Garbinato
Finding trajectories and discovering motifs that are similar in large datasets is a central problem for a wide range of applications. Solutions addressing this problem usually rely…
Capstone: Mobility Modeling on Smartphones to Achieve Privacy by Design
Vaibhav Kulkarni, Arielle Moro, Bertil Chapuis +1
Sharing location traces with context-aware service providers has privacy implications. Location-privacy preserving mechanisms, such as obfuscation, anonymization and cryptographic…
Discovering demographic data of users from the evolution of their spatio-temporal entropy
Arielle Moro, Benoît Garbinato, Valérie Chavez-Demoulin
Inferring information related to users enables to highly improve the quality of many mobile services. For example, knowing the demographic characteristics of a user allows a servic…