معرفی
Hala Lamdouar is a Research Fellow at the University of Oxford, specifically affiliated with the Institute of Biomedical Engineering (IBME). She works under the supervision of Professor Alison Noble and completed her DPhil (PhD) at Oxford's Visual Geometry Group (VGG), advised by Professor Andrew Zisserman and Professor Weidi Xie. Her academic journey began with an Engineering degree in signal and image processing from ENSEIRB-MATMECA, Bordeaux, France, followed by a Master's in applied mathematics focusing on machine learning and computer vision at Ecole Normale Superieure, Paris, where she also worked on autonomous driving perception solutions for Valeo.
- Education
- Engineering degree, ENSEIRB-MATMECA, Bordeaux
- MSc in Applied Mathematics (MVA), Ecole Normale Superieure
- DPhil (PhD), Visual Geometry Group, University of Oxford
Lamdouar's research centers on Video Understanding through single and multi-modal learning, particularly in clinical settings and challenging datasets. Key contributions include motion segmentation techniques for detecting camouflaged objects, the creation of the MoCA dataset (Moving Camouflaged Animals), and scalable synthetic data pipelines for motion-based object segmentation. Her work combines ConvNets, Transformers, and optical flow analysis to address partial occlusion and motion absence in videos.
Notable achievements include the Best Paper Award at the CVPR Workshop on Robust Video Scene Understanding (2021). She has published in top conferences like BMVC (2021), ICCV (2021), and ACCV (2020), with applications in biomedical imaging, autonomous systems, and unsupervised learning. Additional affiliations include the Centre for Doctoral Training in Autonomous Intelligent Machines & Systems (AIMS).
