University of Cambridge

Mobile Systems Research Lab

The Mobile Systems Research Lab concentrates on aspects related to the efficient and effective use of mobile and wearable systems to understand human behaviour and mobile health. Specifically this encompasses systems research related to efficiency of devices and communcation, novel sensing modalities and devices as well as on device machine learning, on one hand. On the other hand, it deals with the analysis of data generated by sensors and wearables with advanced machine learning techniques. The lab concentrates on applications related primarily to mobile health, fitness and sport.


Recent News

  • Our collaboration with SleepCycle for a new Alzheimer's study is covered here.
  • Cecilia Mascolo has been awarded an EPSRC Open Research Fellowship to work on foundations of hearable computing! Here is our annoucement.
  • Our novel work on exploring the power of Open Respiratory Acoustic Foundation Models will appear in NeurIPS Datasets and Benchmarks Track 2024! Read our blog!
  • Our Seminar Series on Mobile and Wearable Health is restarting. Recordings of previous talks here.
  • Our paper "TinyTTA: Efficient Test-time Adaptation via Early-exit Ensembles on Edge Devices" was accepted at NeurIPS24.
  • Our paper TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge has been accepted at ICML24.
  • Our Covid Sounds Work won the Department's Better Future Award this year! Coverage here.
  • Our paper "Machine Learning Detects Altered Spatial Navigation Features in Outdoor Behaviour of Alzheimer’s Disease Patients" was published in Nature Scientific Reports. See publication page for details.
  • Our paper "Sounds of COVID-19: exploring realistic performance of audio-based digital testing" publshed in Npj Digital Medicine is covered in this blog post.
  • Prof Mascolo's University of Oxford Strachey Lecture talk can be found here.
  • Our paper on On-Device Emotion Recognition won the 10-Year Impact Award at ACM Ubicomp!