- PhD Candidate
I am a PhD candidate at the Department of Computer Science and Technology of the University of Cambridge, focusing on Machine Learning and Artificial Intelligence. With my supervisor, Prof. Cecilia Mascolo, I am investigating the automation of the ML pipeline for sparse, unlabelled, and out-of-distribution data. My interests span the areas of uncertainty estimation, AutoML, Active Learning, and addressing distribution shifts in time series data with AI, while I am always open to exploring new promising topics.
Prior to starting my PhD studies, I completed an MRes in Sensor Technologies and Applications and an MPhil in Advanced Computer Science, both from the University of Cambridge. I also hold a BSc in Computer Science from University College London (UCL).
Research
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Mobile Systems
- Time Series Data
- Real-World Data
- Active Learning
- AutoML
- Semi-Supervised Learning
Publications
- SALTS: Streamlined Adaptive Learning for Sensors Time Series. In Proceedings of the 47th IEEE Engineering in Medicine & Biology Conference (EMBC), 2025. Copenhagen, Denmark.
- SQUIREDL: Sparse Sequence-to-Sequence Uncertainty Estimation in Evidential Deep Learning. ACM Transactions on Computing for Healthcare, vol. 6, no. 3. 2025.
- Benchmarking Foundation Models on Out-of-Distribution Wearable Biosignals. 7th UK Mobile, Wearable & Ubiquitous Systems Research Symposium (MobiUK), 2025. Edinburgh, Scotland.
- Uncertainty Estimation with Data Augmentation for Active Learning Tasks on Health Data. In Proceedings of the 45th IEEE Engineering in Medicine & Biology Conference (EMBC), 2023. Sydney, Australia.
- Uncertainty Estimation for Sequence-to-Sequence Regression on Sparse Time Series. 5th UK Mobile, Wearable & Ubiquitous Systems Research Symposium (MobiUK), 2023. Lancaster, England.
