Durham, England, United Kingdom
I'm an AI Research Engineer/Scientist at Intel, specifically working on self-supervised anomaly detection and localization for industrial, medical and security applications. My primary research interests are real-time image classification, detection, anomaly detection, and unsupervised feature learning via deep/machine learning algorithms. We recently open-sourced anomalib, one of the largest anomaly detection libraries in the field. Prior to joining Intel, I worked as a Deep Learning Engineer at COSMONiO where I designed and developed the self-supervised anomaly classification, detection, and segmentation in NOUS, world's first interactive deep learning box for subject matter experts. I finished my PhD degree in the Department of Computer Science at Durham University, UK and received my MSc degree from the Robust Machine Intelligence Lab at the Department of Electrical Engineering at Penn State University, USA. During my PhD, we have published numerous academic papers in the leading computer vision and machine/deep learning conferences and journals and contributed to several projects funded by the UK Home Office, Department for Transport, and the Ministry of Defence.