- Digital healthcare
- Embedded AI
- Signal Processing
- Mobile Systems
My work with health and life sciences at Southampton: Building efficient and scalable diagnostics techniques for respiratory health. Designing machine learning solutions for effective predictive outcomes in cancer sciences.
Covid-19 work: Large crowdsource data collection of audio sounds to build predictive models and contribute to the early diagnosis of COVID-19. (2020 - Ongoing) https://www.covid-19-sounds.org/en/
Medication Adherence: Working with Public Health department (University of Cambridge) to develop a scalable low-cost intervention to support medication adherence in people who are prescribed treatment for certain illnesses in primary care. (2018 - Ongoing)
- Optimizing machine learning for embedded devices: Ongoing. With University of Cambridge and Samsung AI.
- With PhD students, I am also exploring the areas of vital sign monitoring, sensing for fitness and rehab, optimizing federated learning methods and investigating security issues in embedded hardware.