Scholar
Amir Atapour-Abarghouei
Google Scholar ID: 1PuXgDoAAAAJ
Department of Computer Science, Durham University
Citations & Impact
Citations
4,280
H-index
18
i10-index
29
Publications
20
Co-authors
20
list available
Contact
No contact links provided.
Publications
Resume (English only)
Background
- Conducts cutting-edge machine learning research to develop algorithms, systems, and tools that operate robustly in real-world settings.
- Research areas include fundamental deep learning, biodiversity monitoring, precision agriculture, public health and vector surveillance, medical imaging, security, and sustainable transport.
- Core research pillars: Perception and Autonomy (neuromorphic/event-based sensing, mapping and localization, embedded decision-making); Efficient and Trustworthy Learning (robustness under distribution shift, bias and fairness auditing, interpretable models, safety validation); Sensing and Information Fusion (principled multimodal fusion, uncertainty quantification, active sensing, observability/identifiability analysis).
- Interdisciplinary and impact-driven, collaborating with biologists, clinicians, engineers, industry, and public bodies.
- Committed to open science by releasing datasets, benchmarks, and code to accelerate real-world translation.
