Senior Researcher at ISTI-CNR
PhD in Computer Science from University of Pisa in 1998
Dr. Chiara Renso (Female, Google Scholar H-index is 31, Scopus H-index 23, ORCID 0000-0002-1763-2966) is a senior researcher at the ISTI Institute of CNR (Italy) holding a PhD in Computer Science. She has more than 100 peer reviewed publications in the area of mobility data mining, machine learning and and artificial intelligence methods for mobility data, analysis of geolocated social media, semantic enrichment of trajectory data, privacy in mobility data. The focus is addressing interesting, often yet unsolved problems, related to the enrichment, representation, analysis of semantic rich trajectory data, also considering privacy and ethical aspects. She has been the project coordinator of national, International and European Commission projects. Currently, she is the coordinator of a H2020-MSCA-RISE project called MASTER on multiple aspects trajectories management and analysis.
She has been local chair of the IEEE ICDM conference in 2008, local co-chair of the SIGIR conference in 2016. She has been co-chair of the workshops: SADM 2008, SADM 2009, SADM 2010 in conjunction with ICDM conference editions. She has been co-chair of three editions of the Workshop on Big Mobility Data Analytics (BMDA) held in conjunction with EDBT 2019, EDBT 2020, EDBT2021 and three editions of FATES on the Web – International Workshop on Fairness, Accountability, Transparency, Ethics and Society on the Web – in conjunction with The Web Conference. She is co-chair of the special track “Web4Good”at The Web Conference 2022. She has been Workshop Chair of IEEE Mobile Data Management Conference 2020.
She is on the Editorial Board of the International Journal of GIS. She is in the PhD board of the PhD program of Computer Science of the University of Pisa.
She is expert evaluator for the European Commission.
She is Coordinator of the project MASTER (H2020-MSCA-RISE-2017 |2018-2023 – contract N. 777695).
MASTER is a EC funded under the H2020 Marie-Slodowska Curie actions as the RISE funding scheme. The objective is to form an international and inter-sectoral network of organisations working on a joint research programme to define new methods to build, manage and analyse multiple aspects semantic trajectories. We propose methods to analyze and infer knowledge from multiple aspects trajectories, considering as vital issues the privacy and big data dimensions.
She is currently involved in European and National Projects:
The project will explore the potential for an aggregated electric vehicle (EV) charging optimisation in a campus/shared facility leveraging a rich set of data resources for building energy consumption, vehicle operation and parking and wholesale electricity pricing.
MobiDataLab is the EU-funded lab for prototyping new mobility data sharing solutions. Our aim is to foster data sharing in the transport sector, providing mobility organising authorities with recommendations on how to improve the value of their data, contributing to the development of open tools in the cloud, and organising hackathons aiming to find innovative solutions to concrete mobility problems.
Recent selected publications
Chiara Renso, Vania Bogorny, Konstantinos Tserpes, Stan Matwin, José Antônio Fernandes de Macêdo: Multiple-aspect analysis of semantic trajectories(MASTER). Int. J. Geogr. Inf. Sci. 35(4): 763-766 (2021)
Regis Pires Magalhães, Francesco Lettich, José Antônio Fernandes de Macêdo, Franco Maria Nardini, Raffaele Perego, Chiara Renso, Roberto Trani: Speed prediction in large and dynamic traffic sensor networks. Inf. Syst. 98: 101444 (2021)
Ronaldo dos Santos Mello, Geomar Andre Schreiner, Cristian Alexandre Alchini, Gustavo Gonçalves dos Santos, Vania Bogorny, Chiara Renso: Dependency Rule Modeling for Multiple Aspects Trajectories. ER 2021: 123-132
Zaineb Chelly Dagdia, Chiara Renso, Karine Zeitouni, Nazim Agoulmine: Towards a Federated Learning Approach for Privacy-aware Analysis of Semantically Enriched Mobility Data. FRAME@HPDC 2021: 17-20
Lucas May Petry, Camila Leite da Silva, Andrea Esuli, Chiara Renso, Vania Bogorny: MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings. Int. J. Geogr. Inf. Sci. 34(7): 1428-1450 (2020)
Hung Cao, Monica Wachowicz, Chiara Renso, Emanuele Carlini: Analytics Everywhere: Generating Insights From the Internet of Things. IEEE Access 7: 71749-71769 (2019)
Vinicius Monteiro de Lira, Craig Macdonald, Iadh Ounis, Raffaele Perego, Chiara Renso, Valéria Cesário Times: Event attendance classification in social media. Inf. Process. Manag. 56(3): 687-703 (2019)
Christine Parent, Stefano Spaccapietra, Chiara Renso, Gennady L. Andrienko, Natalia V. Andrienko, Vania Bogorny, Maria Luisa Damiani, Aris Gkoulalas-Divanis, José Antônio Fernandes de Macêdo, Nikos Pelekis, Yannis Theodoridis, Zhixian Yan: Semantic trajectories modeling and analysis. ACM Comput. Surv. 45(4): 42:1-42:32 (2013)
Full list of publications: DBLP (https://dblp.org/pid/84/4085.html) and Scholar (https://scholar.google.com/citations?user=y-9deuAAAAAJ&hl=en)