Dr Ahmed Karam Eldaly

I am accepting highly motivated undergrad/MSc/PhD students and research fellows. Please drop me an email if you are interested in working/collaborating with me.

I am a Lecturer (Assistant Professor) in Computer Vision and Artificial Intelligence at the Department of Computer Science, University of Exeter. I am also an Honorary Lecturer in Computer Science at University College London (UCL). My primary research interests encompass computational imaging, machine learning, and statistical signal and image processing, with a particular focus on Bayesian inference, hierarchical models, Markov chain Monte Carlo methods, convex optimisation, and sparse representation, applied in inverse problems, and uncertainty quantification. 

Before that, I was a Research Fellow in Medical Image Analysis at the Centre for Medical Image Computing, Department of Computer Science, Faculty of Engineering Sciences, University College London. I was part of the Welcome-Leap project, a 45 million USD interdisciplinary project spanning universities in the UK, US, South Africa, and other countries. The project’s objective was to build a fully integrated model and measurement tools for network development to predict critical cognitive abilities before a child’s first birthday. Before UCL, I was a Research Fellow in computational imaging at Heriot-Watt University and the University of Edinburgh, as part of the £4M UDRC project. This project involved four universities, and aimed to develop new signal processing and machine learning tools applicable to both the defence and healthcare sectors.

I was awarded a two-year scholarship by the European Commission to obtain an Erasmus Mundus joint master’s degree in computer vision and robotics (VIBOT). I spent the first semester at Université de Bourgogne, France; the second semester at Universität de Girona, Spain; the third semester at Heriot-Watt University, UK, and the final semester with Le2i Laboratory, UB, France. In October 2018, I was awarded the PhD in Electrical, Electronic and Computer Engineering jointly with School of Engineering and Physical Sciences, HWU, and The Queen’s Medical Research Institute, The University of Edinburgh.