Blockchains such as Solana, Sui, and Aptos execute the transactions of a block in parallel, serialising only those that conflict...

Modern edge AI systems increasingly rely on hierarchical inference: a compact on-device model runs first, and only uncertain inputs are...

Android’s permission model is designed around two fundamental guarantees: applications should obtain user consent before accessing sensitive resources, and users...

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...