I am a Research Assistant at
Max Planck Institute for Informatics in Saarbrucken, Germany,
and a Master's student in Computer Science at Saarland University.
My research focuses on Computer Vision and Deep Learning,
Beyond work, I enjoy hiking, photography, and gaming.
News
Feb 2026: Paper accepted at CVPR 2026.
Nov 2025: Paper accepted at 3DV 2026.
Research
My research focus lies at the intersection of Computer Vision and Deep Learning.
In particular, I am interested in the following topics:
Neural Rendering and 3D Head Avatars
Human Pose and Motion Generation
Egocentric 3D Vision
Multi-modal Generative AI
Event Cameras
Publications
E-3DPSM: A State Machine for Event-based Egocentric 3D Human Pose Estimation
We introduce E3DPSM (Event-based 3D Pose State Machine), an event-driven continuous pose state machine for egocentric 3D human pose estimation. By aligning motion dynamics with asynchronous event streams, it produces stable, drift-free pose estimates in real time (80 Hz). Our method sets a new state of the art, improving accuracy by up to 19% and temporal stability by 2.7x.
GRMM: Real-Time High-Fidelity Gaussian Morphable Head Model with Learned Residuals
Our method, GRMM (Gaussian Residual Morphable Model), generates high-fidelity 3D head avatars in real time by combining a mesh-based morphable prior with learned Gaussian residuals. This design captures fine geometric and appearance details while maintaining disentangled control over identity and expression, enabling photorealistic and expressive facial synthesis.
Projects
PhotonPulse
PhotonPulse is a C++ physically based renderer with support for cameras, BSDFs, samplers, lights, integrators, and post-processing features such as denoising and bloom.
SceneChat is a text-driven scene generation pipeline that turns a natural language description into a structured room layout, previews the layout in Blender, and can generate 3D assets for the objects in the scene.
This project implements a semantic, perceptual image compression pipeline that uses a convolutional model to identify regions of interest in an image and allocate compression quality accordingly.