Deep learning PhD researcher working on computer vision for 3D and time-resolved data, physics-informed training, multimodal biomedical data (CT/MRI, whole-slide images, omics), and LLM / VLM agents and evaluation.
Highlights
- 🧩 biomechanical_DLIR: PyTorch framework for physically constrained image deformation learning (rigidity, sliding, learned tissue mechanics). Scientific Reports 2026. Try it live on Hugging Face
- ⏱️ IMITATE: conditional network that reconstructs missing frames in 3D time sequences (IEEE ISBI 2025, oral)
- 🏆 VisioMel: 2nd place, melanoma relapse prediction from gigapixel slide images
- 💬 Elenchus: multiplayer LLM workspace (TypeScript), deployed on
I enjoy understanding new things, from science to chess.
- 🤔 Always happy to collaborate on data-driven scientific discovery in oncology and healthcare, and on physics-informed / constrained learning.
- ☕️ Often up for a coffee break.

