The SmartData@PoliTO center focuses on Big Data technologies, Data Science and Machine Learning approaches.
We blend interdisciplinary people and competences from different domains to provide cross-domain solutions to the widest spectrum of knowledge discovery challenges, by leveraging advanced expertise in data science, from data management, to data modeling, analytics, and engineering.
We are a well-recognized center where experts in methodologies and domain experts from various disciplines work in a single space, facing both theoretical problems and helping companies toward applications.

Open Datasets & Libraries

ODySSEUS an Origin-Destination Simulator of Shared E-mobility in Urban Scenarios

Introduction ODySSEUS is a mobility simulation software focused on shared fleets in urban environments. Its goal is to provide a general, easy-to-use framework to simulate shared mobility scenarios across different cities using real-world data. ODySSEUS is composed by four main functional modules, each one coming with its own API, command line interface and GUI: City […]

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SmartTalks

Reconstructing epidemic cascades with autoregressive neural networks

Presenter: Fabio MazzaThursday, April 15th, 2021 17:30Location: Microsoft Teams – click here to join Fabio Mazza: Reconstructing epidemic cascades with autoregressive neural networks In the case of inference of epidemic spreading of a disease, we usually have missing or partial information on an epidemic cascade. In order to understand, characterize and mitigate the spreading of […]

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Open Datasets & Libraries

Real-Time Classification of Real-Time Communications

This webpage contains additional material of the paper: “Real-Time Classification of Real-Time Communications“ (currently under revision) Year: 2021 Authors: Gianluca Perna, Dena Markudova, Martino Trevisan, Michela Meo, Paolo Garza, Maurizio Munafò, Giovanna Carofiglio The data You can find the dataset and the classifiers on this link: Data and classifiers The link contains: webex_dataset.csv – a […]

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Open Datasets & Libraries

Discrete Fracture Network Flow Simulations

This repository contains data and information regarding the paper: Stefano Berrone and Francesco Della Santa, “Performance Analysis of Multi-Task Deep Learning Models for Flux Regression in Discrete Fracture Networks” (to appear on the special issue “Quantitative Fractured Rock Hydrology” of Geosciences, ISSN 2076-3263). Summary: Analysis of underground flows in fractured media is relevant in several […]

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