Cecilia Mascolo

University College London, University of Cambridge

Papers

Total Citations

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About

Cecilia Mascolo is a leading researcher in mobile sensing, embedded machine learning, and ubiquitous computing. Her work has fundamentally advanced how sensor data is collected and processed in dynamic, resource-constrained environments. A key contribution is the SCAR protocol (77 citations), which pioneered opportunistic mobile sensor data collection from moving devices like phones and vehicles, addressing the challenge of network topology variability. More recently, she has driven innovation in on-device intelligence with LifeLearner (2023), a hardware-aware meta continual learning system that enables embedded platforms to adapt on the fly despite limited resources. Mascolo has also broken new ground in wearable sensing, particularly with her work on earables—in-ear wearables that serve as both audio devices and sensing platforms. Her magnetometer calibration system (2021) makes ear-based magnetic sensing automatic and user-transparent, opening new possibilities for upper-body health and activity monitoring. With hundreds of citations across her portfolio, Mascolo’s research bridges the gap between theoretical advances and practical, deployable systems, making her a pivotal figure in the future of intelligent, context-aware mobile and wearable technology.