Michal Irani

Prof. Michal Irani is a Professor in the Department of Computer Science and Applied Mathematics, conducting cutting-edge research in image processing, computer vision, video analysis, deep learning, and artificial intelligence.

Her work centers on six core themes:

• The Internal Statistics of Natural Images and Videos
• Visual Inference by Composition
• Space-Time Analysis of Video
• Deep Internal Learning: training deep networks on single natural images/videos
• Mind Reading: reconstructing visual data from fMRI brain activity
• Reconstructing training data from trained neural networks

These interdisciplinary efforts bridge computer science with neuroscience and machine learning, emphasizing novel approaches to visual data synthesis and interpretation from minimal input sources.

Her complete publication record is accessible via her dedicated publications section.