Eyal de Lara

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About

Eyal de Lara is a leading researcher in mobile and ubiquitous computing, with a focus on systems that bridge the physical and digital worlds. His work spans deep reinforcement learning (RL) systems, mobile sensing, and pervasive computing infrastructure. In his highly cited paper "RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads" (2021, 4 citations), de Lara identified fundamental structural differences in RL workloads that create unique system-level bottlenecks—a critical contribution as RL transforms robotics and data center management. As editor of *IEEE Pervasive Computing*, he has shaped the field by curating innovations such as ubiquitous city initiatives, virtual world design, and mobile phone network data for traffic analysis (2006–2007, 5+ combined citations). His editorial work highlights technologies like Bluetooth-integrated car audio and wind-harvesting electricity, demonstrating his talent for spotting practical, impactful systems. With a career dedicated to understanding how mobile and embedded systems interact with real-world environments, de Lara’s contributions help researchers and engineers build more efficient, context-aware computing platforms.