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Complex systems are increasingly being viewed as distributed information processing systems, particularly in the domains of computational neuroscience, bioinformatics and Artificial Life. This trend has resulted in a strong uptake in the…
Bayesian Knowledge Tracing, a model used for cognitive mastery estimation, has been a hallmark of adaptive learning research and an integral component of deployed intelligent tutoring systems (ITS). In this paper, we provide a brief history…
Understanding how people move in the urban area is important for solving urbanization issues, such as traffic management, urban planning, epidemic control, and communication network improvement. Leveraging recent availability of large…
Statistics about traffic flow and people's movement gathered from multiple geographical locations in a distributed manner are the driving force powering many applications, such as traffic prediction, demand prediction, and restaurant…
Preserving user privacy is paramount when it comes to publicly disclosed datasets that contain fine-grained data about large populations. The problem is especially critical in the case of mobile traffic datasets collected by cellular…
In this chapter, we discuss urban mobility from a complexity science perspective. First, we give an overview of the datasets that enable this approach, such as mobile phone records, location-based social network traces, or GPS trajectories…
swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidates functionality across multiple domains, including data…
Trip data that records each vehicle's trip activity on the road network describes the operation of urban traffic from the individual perspective, and it is extremely valuable for transportation research. However, restricted by data privacy,…
PeopleTraffic is a proposed initiative to develop a real-time, open-data population density mapping tool open to public institutions, private companies and the civil society, providing a common framework for infection spreading prevention.…
Building simulation environments for developing and testing autonomous vehicles necessitates that the simulators accurately model the statistical realism of the real-world environment, including the interaction with other vehicles driven by…
We present a scalable solution to link entities across mobility datasets using their spatio-temporal information. This is a fundamental problem in many applications such as linking user identities for security, understanding privacy…
With the urbanization process, an increasing number of sensors are being deployed in transportation systems, leading to an explosion of big data. To harness the power of this vast transportation data, various machine learning (ML) and…
Nowadays, human movement in urban spaces can be traced digitally in many cases. It can be observed that movement patterns are not constant, but vary across time and space. In this work,we characterize such spatio-temporal patterns with an…
Effective driving style analysis is critical to developing human-centered intelligent driving systems that consider drivers' preferences. However, the approaches and conclusions of most related studies are diverse and inconsistent because…
Differential privacy is a mathematical concept that provides an information-theoretic security guarantee. While differential privacy has emerged as a de facto standard for guaranteeing privacy in data sharing, the known mechanisms to…
MobilitApp is an Android application whose objective is to obtain mobility data from the citizens of the metropolitan area of Barcelona. The current project is based on the research of more trustful and stronger transport decision…
The description of complex human mobility patterns is at the core of many important applications ranging from urbanism and transportation to epidemics containment. Data about collective human movements, once scarce, has become widely…
The number and variety of Internet-connected devices have grown enormously in the past few years, presenting new challenges to security and privacy. Research has shown that network adversaries can use traffic rate metadata from consumer IoT…
Human mobility data has been ubiquitously collected through cellular networks and mobile applications, and publicly released for academic research and commercial purposes for the last decade. Since releasing individual's mobility records…
Cities are living systems where urban infrastructures and their functions are defined and evolved due to population behaviors. Profiling the cities and functional regions has been an important topic in urban design and planning. This paper…