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Beyond Interruptibility: Predicting Opportune Moments to Engage Mobile Phone Users.

, , , , , and . Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 1 (3): 91:1-91:25 (2017)

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Deep Private-Feature Extraction., , , , , and . CoRR, (2018)BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices., , , , and . HotNets, page 101-108. ACM, (2019)BatteryLab: A Collaborative Platform for Power Monitoring - https: //batterylab.dev., , , , , and . PAM, volume 13210 of Lecture Notes in Computer Science, page 97-121. Springer, (2022)Demo: Detecting Group Formations using iBeacon Technology., , , , and . MobiSys, page 190. ACM, (2017)Walking in Sync: Two is Company, Three's a Crowd., , , and . WPA@MobiSys, page 25-29. ACM, (2015)Poster: SensingKit: a multi-platform mobile sensing framework for large-scale experiments., , and . MobiCom, page 375-378. ACM, (2014)Poster: Towards Characterizing and Limiting Information Exposure in DNN Layers., , , , and . ACM Conference on Computer and Communications Security, page 2653-2655. ACM, (2019)Analysing crowd behaviours using mobile sensing.. Queen Mary University of London, UK, (2018)British Library, EThOS.P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups., , , and . CoRR, (2023)BatteryLab, a distributed power monitoring platform for mobile devices: demo abstract., , , , , , and . SenSys, page 386-387. ACM, (2019)