Maria Luisa Damiani
My research interests lie at the intersection of spatial computing, mobility data science and data protection. Current research focuses primarily on the study of behavior patterns in traces of people and animals. Behavior patterns are of primary interest in a variety of applications, e.g., visitor profiling, computational sociology, security, animal ecology. Behavior analysis requires the observation of real world mobility phenomena, the development of data models and analytical tools, the investigation of quality metrics and benchmarking. An additional stream of research aims to bridge spatial computing and cybersecurity, focusing on location-based security for authentication, access control, privacy, for use in mobile applications. The deployment of these methods in real application is another major challenge. In summary, the main contributions and artifacts developed in my research are :
A framework for the discovery of stop-move patterns in trajectories (data from UWB, GNSS, Telco data) . It includes: the SeqScan family of stop detection techniques for the segmentation of continuous and discrete trajectories; quality metrics for the evaluation of stop-move patterns; stop-driven analytics for individuals, groups and POI profiling; benchmarking.
Data models for the high-level representation of mobility data: the Semantic Trajectory conceptual data model; the Symbolic Trajectory logical data model; query models for Symbolic Trajectories processing
Location-based access control: the Geo-RBAC model and its extensions, Geo-RBAC has been a pioneering model in access control, compliant with the RBAC standard
Location privacy: the PROBE technique for semantic location obfuscation in free and network spaces, The technique targets location protection against background knowledge
Applications in a variety of domains, including:
- animal ecology: MigrO, a plugin for migration analysis from low sampled GPS trajectories
- museums: platform for the behavior analysis of visitors from UWB trajectories
- geology: Etna Lava Flow Model (EFLM), a simulator of volcanic lava flows
M.L. Damiani graduated in Computer Science from University of Pisa cum laude and earned a Ph.D in Computer Science from EPFL. Prior to joining academia in 2003, she held various positions in applied research in public and private companies (CSELT, Datamont Spa, Elda Ingegneria Spa), working in several European Research Projects mostly on knowledge representation topics, first as researcher, then as Local PI and Project Manager (Esprit Esteam, Itacha 1, ADKMS, Business Class, AIMS). Moreover, she was co-founder of a start-up operating in the area of geographical information systems in civil engineering. In academia, she has been a visiting researcher at EPFL (2007) and at Purdue University (2006, 2016, 2017). She worked in the European research projects: FP6 GeoPKDD as EPFL sub-contractor; FP7 Modap (Mobility Data Mining and Privacy); and COST Action Move (Knowledge Discovery from Moving Objects). She was/is working in national research projects funded by Ministry of Research: PRIN Next-generation Ultra-wideband Localization and Communication for the Internet of Things [ 2019-Aug 2023]; and MUR PNRR Serics - Security and Rights in Cyberspace (Jan 2023-2025). She is associate editor for ACM TSAS and Springer GeoInformatica, and from 2017 to 2022 associate editor for IEEE TDSC. She served as PC Co-Chair in IEEE Mobile Data Management 2023 and General Co-Chair in ACM SIGSpatial 2023. Currently, she serves as member of the Executive Committee @ ACM Special Interest Group on Spatial Information (https://www.sigspatial.org/).