| Designing Memory Aids for Dementia Patients using Earables | 0 | 0.34 | 2021 |
| Chronic Pain Protective Behavior Detection with Deep Learning | 0 | 0.34 | 2021 |
| Leveraging Activity Recognition to Enable Protective Behavior Detection in Continuous Data. | 1 | 0.34 | 2021 |
| Unsupervised Domain Adaptation Under Label Space Mismatch for Speech Classification. | 0 | 0.34 | 2020 |
| Data4Good - Designing for Diversity and Development. | 0 | 0.34 | 2020 |
| Situation-Aware Conversational Agent with Kinetic Earables | 0 | 0.34 | 2019 |
| Situation-Aware Emotion Regulation of Conversational Agents with Kinetic Earables | 0 | 0.34 | 2019 |
| Automatic Smile and Frown Recognition with Kinetic Earables | 2 | 0.36 | 2019 |
| Recurrent network based automatic detection of chronic pain protective behavior using MoCap and sEMG data | 4 | 0.43 | 2019 |
| An early characterisation of wearing variability on motion signals for wearables | 1 | 0.54 | 2019 |
| Automatic Detection of Protective Behavior in Chronic Pain Physical Rehabilitation: A Recurrent Neural Network Approach. | 0 | 0.34 | 2019 |
| AudiDoS - Real-Time Denial-of-Service Adversarial Attacks on Deep Audio Models. | 0 | 0.34 | 2019 |
| Unsupervised domain adaptation for robust sensory systems | 0 | 0.34 | 2019 |
| FlexAdapt - Flexible Cycle-Consistent Adversarial Domain Adaptation. | 0 | 0.34 | 2019 |
| A closer look at quality-aware runtime assessment of sensing models in multi-device environments | 1 | 0.35 | 2019 |
| A Vision for Adaptive and Generalizable Audio-Sensing Systems. | 0 | 0.34 | 2019 |
| Audio-Kinetic Model for Automatic Dietary Monitoring with Earable Devices. | 1 | 0.34 | 2018 |
| Earables for Personal-Scale Behavior Analytics. | 8 | 0.83 | 2018 |
| Exploring audio and kinetic sensing on earable devices. | 0 | 0.34 | 2018 |
| eSense: Earable Platform for Human Sensing. | 1 | 0.41 | 2018 |
| Cross-Modal Approach for Conversational Well-being Monitoring with Multi-Sensory Earables. | 0 | 0.34 | 2018 |
| Squeezing Deep Learning into Mobile and Embedded Devices. | 23 | 0.83 | 2017 |
| Moving Beyond Market Research: Demystifying Smartphone User Behavior in India. | 1 | 0.41 | 2017 |
| DeepEye: Resource Efficient Local Execution of Multiple Deep Vision Models using Wearable Commodity Hardware. | 17 | 0.69 | 2017 |
| Towards cognitive awareness: a mobile context modeling- and notification-based approach. | 1 | 0.35 | 2017 |
| Application overchoice: preliminary lessons from a longitudinal study. | 1 | 0.35 | 2017 |
| The Need to Account for Geographical Diversities in Mobile Data Research | 0 | 0.34 | 2016 |
| DXTK: Enabling Resource-efficient Deep Learning on Mobile and Embedded Devices with the DeepX Toolkit | 5 | 0.61 | 2016 |
| Understanding the impact of personal feedback on face-to-face interactions in the workplace. | 3 | 0.65 | 2016 |
| Understanding the Privacy Design Space for Personal Connected Objects. | 0 | 0.34 | 2016 |
| Engagement-aware computing: modelling user engagement from mobile contexts. | 8 | 0.46 | 2016 |
| A case study on capturing and visualising face-to-face interactions in the workplace. | 1 | 0.35 | 2016 |
| Tiny habits in the giant enterprise: understanding the dynamics of a quantified workplace | 14 | 0.82 | 2015 |
| Quantified Workplace: Opportunities and Challenges | 2 | 0.36 | 2015 |
| The myth of subtle notifications. | 6 | 0.55 | 2014 |
