Senior Scientist, ETH Zürich
Computer Vision · 3D/4D Reconstruction · Spatial Intelligence
I study how machines can build useful internal models of the physical world, from 3D geometry and 4D dynamics to structured representations for spatial reasoning.
I am a senior scientist at ETH Zürich, working at the intersection of computer vision, computer graphics, and machine learning. My research focuses on representations of real-world 3D and 4D phenomena: reconstructing geometry, modelling motion, rendering photorealistic scenes, and extracting structure from visual observations.
I am increasingly focused on spatial intelligence: the bridge between geometric reconstruction and higher-level reasoning. My goal is to develop models that form and update internal maps to answer fundamental questions: what is where, what changes, and how can a machine interact with its environment?
Methods for reconstructing and rendering photorealistic static and dynamic scenes from sparse or imperfect observations.
Efficient representations for geometry, appearance, motion, and time-varying real-world structure.
Digital representations of humans, biological systems, and surgical scenes: controllable, temporally coherent, and grounded in real observations.
Understanding what kinds of internal maps vision models need for reasoning about space, objects, motion, navigation, interaction, and change.
At ETH Zürich, I co-teach Computer Vision (with Marc Pollefeys and Siyu Tang) and Digital Humans (with Siyu Tang).
I supervise student projects in computer vision, 3D reconstruction, neural rendering, and spatial intelligence, with particular interest in work that connects rigorous geometric modelling with modern foundation models.
If you are a student interested in working on these topics, please reach out. The most useful messages are short and specific: what you want to work on, why it interests you, and what you have already tried.