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Vanessa Frias-Martinez

Bio: Vanessa Frias-Martinez is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Population & Phone. The author has an hindex of 22, co-authored 65 publications receiving 1742 citations. Previous affiliations of Vanessa Frias-Martinez include Telefónica & Columbia University.


Papers
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Proceedings ArticleDOI
03 Sep 2012
TL;DR: This paper evaluates the use of geolocated tweets as a complementary source of information for urban planning applications and applies techniques to automatically determine land uses in a specific urban area based on tweeting patterns.
Abstract: The pervasiveness of cell phones and mobile social media applications is generating vast amounts of geolocalized user-generated content. Since the addition of geotagging information, Twitter has become a valuable source for the study of human dynamics. Its analysis is shedding new light not only on understanding human behavior but also on modeling the way people live and interact in their urban environments. In this paper, we evaluate the use of geolocated tweets as a complementary source of information for urban planning applications. Our contributions are focussed in two urban planing areas: (1) a technique to automatically determine land uses in a specific urban area based on tweeting patterns, and (2) a technique to automatically identify urban points of interest as places with high activity of tweets. We apply our techniques in Manhattan (NYC) using 49 days of geolocated tweets and validate them using land use and landmark information provided by various NYC departments. Our results indicate that geolocated tweets are a powerful and dynamic data source to characterize urban environments.

212 citations

Journal ArticleDOI
TL;DR: The proposed technique uses unsupervised learning and automatically determines land uses in urban areas by clustering geographical regions with similar tweeting activity patterns, indicating that geolocated tweets can be used as a powerful data source for urban planning applications.

181 citations

Proceedings ArticleDOI
01 Oct 2011
TL;DR: An agent-based system that uses social interactions and individual mobility patterns extracted from call detail records to accurately model virus spreading is proposed and applied to study the 2009 H1N1 outbreak in Mexico and to evaluate the impact that government mandates had on the spreading of the virus.
Abstract: The recent adoption of ubiquitous computing technologies has enabled capturing large amounts of human behavioral data The digital footprints computed from these datasets provide information for the study of social and human dynamics, including social networks and mobility patterns, key elements for the effective modeling of virus spreading Traditional epidemiologic models do not consider individual information and hence have limited ability to capture the inherent complexity of the disease spreading process To overcome this limitation, agent-based models have recently been proposed as an effective approach to model virus spreading However, most agent-based approaches to date have not included real-life data to characterize the agents' behavior In this paper we propose an agent-based system that uses social interactions and individual mobility patterns extracted from call detail records to accurately model virus spreading The proposed approach is applied to study the 2009 H1N1 outbreak in Mexico and to evaluate the impact that government mandates had on the spreading of the virus Our simulations indicate that the restricted mobility due the government mandates reduced by 10% the peak number of individuals infected by the virus and postponed the peak of the pandemic by two days

168 citations

Proceedings ArticleDOI
11 Jul 2011
TL;DR: Predictive models constructed with SVMs and Random Forests that use the aggregated behavioral variables of the communication antennas to predict socioeconomic levels are presented.
Abstract: The socioeconomic status of a population or an individual provides an understanding of its access to housing, education, health or basic services like water and electricity. In itself, it is also an indirect indicator of the purchasing power and as such a key element when personalizing the interaction with a customer, especially for marketing campaigns or offers of new products. In this paper we study if the information derived from the aggregated use of cell phone records can be used to identify the socioeconomic levels of a population. We present predictive models constructed with SVMs and Random Forests that use the aggregated behavioral variables of the communication antennas to predict socioeconomic levels. Our results show correct prediction rates of over 80% for an urban population of around 500,000 citizens.

126 citations

Proceedings ArticleDOI
12 Mar 2012
TL;DR: A novel analytical approach is proposed that combines large-scale datasets of cell phone records with countrywide census data to reveal findings at a national level and shows correlations between socio-economic levels and social network or mobility patterns among others.
Abstract: The ubiquitous presence of cell phones in emerging economies has brought about a wide range of cell phone-based services for low-income groups. Often times, the success of such technologies highly depends on its adaptation to the needs and habits of each social group. In an attempt to understand how cell phones are being used by citizens in an emerging economy, we present a large-scale study to analyze the relationship between specific socio-economic factors and the way people use cell phones in an emerging economy in Latin America. We propose a novel analytical approach that combines large-scale datasets of cell phone records with countrywide census data to reveal findings at a national level. Our main results show correlations between socio-economic levels and social network or mobility patterns among others. We also provide analytical models to accurately approximate census variables from cell phone records with R2 ≈ 0.82.

85 citations


Cited by
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01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

2,933 citations

01 Aug 2001
TL;DR: The study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence, is concentrated on in this work.
Abstract: With digital equipment becoming increasingly networked, either on wired or wireless networks, for personal and professional use alike, distributed software systems have become a crucial element in information and communications technologies. The study of these systems forms the core of the ARLES' work, which is specifically concerned with defining new system software architectures, based on the use of emerging networking technologies. In this context, we concentrate on the study of distributed systems which bring to life the vision of ubiquitous computing systems, also known as ambient intelligence.

2,774 citations

Journal ArticleDOI
19 Aug 2016-Science
TL;DR: This work shows how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes, and could transform efforts to track and target poverty in developing countries.
Abstract: Reliable data on economic livelihoods remain scarce in the developing world, hampering efforts to study these outcomes and to design policies that improve them. Here we demonstrate an accurate, inexpensive, and scalable method for estimating consumption expenditure and asset wealth from high-resolution satellite imagery. Using survey and satellite data from five African countries—Nigeria, Tanzania, Uganda, Malawi, and Rwanda—we show how a convolutional neural network can be trained to identify image features that can explain up to 75% of the variation in local-level economic outcomes. Our method, which requires only publicly available data, could transform efforts to track and target poverty in developing countries. It also demonstrates how powerful machine learning techniques can be applied in a setting with limited training data, suggesting broad potential application across many scientific domains.

1,089 citations

Journal ArticleDOI
19 Aug 2016-Science
TL;DR: Microscopy of an evolving quantum system indicates that the full quantum state remains pure, whereas thermalization occurs on a local scale, whereas entanglement creates local entropy that validates the use of statistical physics for local observables.
Abstract: Statistical mechanics relies on the maximization of entropy in a system at thermal equilibrium. However, an isolated quantum many-body system initialized in a pure state remains pure during Schrodinger evolution, and in this sense it has static, zero entropy. We experimentally studied the emergence of statistical mechanics in a quantum state and observed the fundamental role of quantum entanglement in facilitating this emergence. Microscopy of an evolving quantum system indicates that the full quantum state remains pure, whereas thermalization occurs on a local scale. We directly measured entanglement entropy, which assumes the role of the thermal entropy in thermalization. The entanglement creates local entropy that validates the use of statistical physics for local observables. Our measurements are consistent with the eigenstate thermalization hypothesis.

1,014 citations

Journal ArticleDOI
21 Aug 2006
TL;DR: An introduction to market-based multirobot coordination is provided, a review and analysis of the state of the art in the field, and a discussion of remaining research challenges are discussed.
Abstract: Market-based multirobot coordination approaches have received significant attention and are growing in popularity within the robotics research community. They have been successfully implemented in a variety of domains ranging from mapping and exploration to robot soccer. The research literature on market-based approaches to coordination has now reached a critical mass that warrants a survey and analysis. This paper addresses this need for a survey of the relevant literature by providing an introduction to market-based multirobot coordination, a review and analysis of the state of the art in the field, and a discussion of remaining research challenges

896 citations