Adel Bibi

Bibi is a PhD candidate in the Image and Video Understanding Lab (IVUL) Group under the supervision of Prof Bernard Ghanem at KAUST.

He has worked on a variety of computer vision and optimization related problems. Problems ranging from visual object tracking and clustering to large scale deterministic/stochastic optimization for machine learning and vision applications.

He has several oral and spotlight papers in CVPR/ICCV/ECCV.

In 2018, he won best KAUST poster award on new tensor factorization strategy for convolutional sparse coding and was recognized as an outstanding reviewer for CVPR18.

Recently, he is interested in analyzing deep networks in probabilistic settings via analytical expressions that may facilitate robust network training.