Dr. Wouter Van Gansbeke

I will be a tenure-track faculty member at INSAIT. 

Contact: [email protected]
Google Scholar: link

My main research interests lie in the area of computer vision. In particular, I currently work on the following domains and their intersections:

  • Understanding Visual Scenes: Modeling geometry, discovering objects and patterns in complex scenes;
  • Self-Supervised Learning: Learn useful representations or groups without annotations by leveraging visual similarities;
  • Generative Learning: Capture the underlying data distribution of images using generative principles;
  • Multi-Modal Learning:  Learn from different modalities, or streams of information, since our world is inherently multi-modal, e.g., leverage vision and text.

I strongly believe that these fields are important to enable machine intelligence and large-scale autonomy as already evidenced in applications such as autonomous driving and augmented reality (AR / VR). If you’re interested in any of the mentioned topics, don’t hesitate to reach out.

Academic degrees:

Recognition – Research Community:

  • Outstanding Reviewer for ECCV 2022 and CVPR 2023.
  • Our ECCV paper received attention from the research community, with multiple YouTube videos and blog posts discussing its findings.
  • Co-organized the workshop ”Deep Multi-Task Learning in Computer Vision (DeepMTL)” at ICCV 2021.

Before, I interned at Meta (Facebook AI Research) in California.