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We propose a novel reliability model for composing energy service requests. The proposed model is based on consumers' behavior and history of energy requests. The reliability model ensures the maximum incentives to providers. Incentives are…
Reliable hydrologic and flood forecasting requires models that remain stable when input data are delayed, missing, or inconsistent. However, most advances in rainfall-runoff prediction have been evaluated under ideal data conditions,…
Researchers find weaknesses in current strategies for protecting privacy in large datasets. Many anonymized datasets are reidentifiable, and norms for offering data subjects notice and consent over emphasize individual responsibility. Based…
Traditional reliability analysis has been using time to event data, degradation data, and recurrent event data, while the associated covariates tend to be simple and constant over time. Over the past years, we have witnessed the rapid…
Selecting customers for demand response programs is challenging and existing methodologies are hard to scale and poor in performance. The existing methods were limited by lack of temporal consumption information at the individual customer…
We propose a scalable Bayesian preference learning method for jointly predicting the preferences of individuals as well as the consensus of a crowd from pairwise labels. Peoples' opinions often differ greatly, making it difficult to predict…
A key challenge in many modern data analysis tasks is that user data are heterogeneous. Different users may possess vastly different numbers of data points. More importantly, it cannot be assumed that all users sample from the same…
We are developing a system for human-robot communication that enables people to communicate with robots in a natural way and is focused on solving problems in a shared space. Our strategy for developing this system is fundamentally…
Assessing whether a sample survey credibly represents the population is a critical question for ensuring the validity of downstream research. Generally, this problem reduces to estimating the distance between two high-dimensional…
Modeling human dynamics responsible for the formation and evolution of the so-called social networks - structures comprised of individuals or organizations and indicating connectivities existing in a community - is a topic recently…
More and more smart devices enter our homes. Often these devices come with a variety of sensors, mostly simple sensors, e.g., for light, temperature, humidity or motion. And they all collect data. While it is data of the home environment it…
Mobile crowdsensing has emerged as an efficient sensing paradigm which combines the crowd intelligence and the sensing power of mobile devices, e.g.,~mobile phones and Internet of Things (IoT) gadgets. This article addresses the…
Population growth is in general constrained by food production, which in turn depends on the access to water resources. At a country level, some populations use more water than they control because of their ability to import food and the…
Smart meters (SMs) measure and report users' energy consumption to the utility provider (UP) in almost real-time, providing a much more detailed depiction of the consumer's energy consumption compared to their analog counterparts. This…
Pedestrian GPS data are key to a better understanding of micro-mobility and micro-behaviour within a neighbourhood. These data can bring new insights into walkability and livability in the context of urban sustainability. However,…
COVID-19 has spread all over the world, having an enormous effect on our daily life and work. In response to the epidemic, a lot of important decisions need to be taken to save communities and economies worldwide. Data clearly plays a vital…
In recent years, the energy-water nexus literature has recognized that the electricity and water infrastructure that enable the production, distribution, and consumption of these two commodities is fundamentally intertwined. Electric power…
Research into, and design and construction of mobile systems and algorithms requires access to large-scale mobility data. Unfortunately, the wireless and mobile research community lacks such data. For instance, the largest available human…
Distributed ledgers are a new type of database technology that allows open access to data stored across distributed, decentralised, publicly maintained infrastructures. Current implementations of the such ledgers expect competition between…
For the modeling, design and planning of future energy transmission networks, it is vital for stakeholders to access faithful and useful power flow data, while provably maintaining the privacy of business confidentiality of service…