Cellular networks support many facets of our everyday lives, ranging from a quick web search on the go to requesting...

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

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...

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

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...

Large-scale social gatherings often generate distinctive patterns of activity in mobile networks due to the concentration of a substantial amount...

On April 28, 2025, the Iberian Peninsula experienced its most severe electrical grid failure on record, causing widespread disruption across...

Radio Access Networks (RANs) are critical infrastructures that mobile operators continuously upgrade to accommodate increasing data traffic demands, stricter performance...