Research

Research

My research focuses on the self-management of decentralized networked systems designed to empower citizens’ participation for a more democratic and sustainable digital society. The pervasiveness of the Internet of Things has brought paramount opportunities to share massive scales of data that fuel smart services and improve several sectors of our society such as energy, transport, health and other. However these opportunities come with several techno-socio-economic challenges that stem from the centralized design and management of information systems in the era of big data and artificial intelligence. The preservation of privacy and autonomy are questioned when data intensive applications require the collection and centralized processing of personal data that can allow profiling actions, discriminatory data analytics as well as nudging by personalized recommender algorithms. Moreover, centralized information systems are complex to manage, scale and adapt in open and dynamic networked environments under uncertainties such as join and leaves, (cascading) failures, system interdependencies and other.

Designing decentralized and self-managed techno-socio-economic systems that can continuously self-adapt, self-heal, self-repair, self-organize and ultimately self-regulate the production and consumption of our resources, e.g. energy, food supplies, sharing vehicles, etc., are means for a sustainable development as I show in my research.

Designing decentralized and self-managed techno-socio-economic systems that can continuously self-adapt, self-heal, self-repair, self-organize and ultimately self-regulate the production and consumption of our resources, e.g. energy, food supplies, sharing vehicles, etc., are means for a sustainable development as I show in my research. Supply-demand data sharing systems self-regulated via differential privacy mechanisms and distributed ledger systems, i.e. blockchain, can protect citizens’ privacy, while incentivizing a fair data sharing for a high quality of service. System-wide, citizens’ active participation and autonomy raises communication and computational challenges: Data streams need to propagate rapidly and regularly in a distributed network. Citizens’ collective choices often have combinatorial complexity. Decentralized optimization and collective learning over crowd-sourced computational resources of citizens is the main challenge of my research. Tackling this challenge can have a tremendous impact on a new generation of artificial intelligence for socio-technical systems equipped with socially responsible self-management capabilities applied on emerging application domains of Smart Grids, Smart Cities and their sharing economies.

artificial intelligence for socio-technical systems equipped with socially responsible self-management capabilities applied on emerging application domains of Smart Grids, Smart Cities and their sharing economies.

For more information, explore my research projects and publications.

Research outline and profile.