The Network Scale-up Method (NSUM) is a technique that emerged as an alternative to traditional survey methods and estimates the...

This thesis contributes to the development of the Network Scale-up Method (NSUM). This technique emerged as an alternative to traditional...

Traditional federated learning (FL) relies on a central aggregator, creating potential performance bottlenecks and privacy risks. Decentralized alternatives remove the...

Can passively collected mobile-network data reveal useful public-health signals during an epidemic, without apps, contact tracing, or individual diagnosis? We...

Energy consumption has become a pressing concern as mobile networks expand rapidly, with the radio access network accounting for the...

What can science do when a fire, flood, earthquake, or accident occurs? In this activity for Madrid’s European Researchers’ Night,...

Wi-Fi sensing enables innovative applications in healthcare and surveillance by providing continuous, contactless monitoring through existing infrastructure. Moreover, exploiting information...

I will present the PIXEurope Pilot Line, a recently started 400MEuro initiative under the Chips JU, that aims at developing...

This thesis investigates how deep neural networks can support reliable mobile traffic forecasting for 5G and future mobile networks. Accurate...

Programmable ASICs enable stateful network functions at line rate, including emerging in-network inference tasks. However, limited on-chip SRAM constrains the...