About Me

I'm a PhD researcher in deep learning and computer vision working on transformer‑driven automation of brain‑cancer treatment—covering segmentation, synthetic imaging, and dose prediction. Below are some of my recent open‑source projects, publications, and teaching resources.

Experience

2022 – Present
PhD Researcher – Aarhus University Hospital

Designing self‑adapting transformer and diffusion models for fully‑automated brain‑cancer treatment planning; collaborating with oncologists to bring prototypes into clinical evaluation.

2024 – 2024
Visiting Researcher – University of Cambridge

Built CNN pipeline for MRI‑based tumour sub‑typing.

2021 – 2022
Researching master student – Aalborg University

Recent Works on GitHub

Clinical‑AI projects and tooling currently maintained.

CBCT → Synthetic CT Diffusion
Stable Diffusion fine‑tuned for CBCT‑to‑CT conversion.
CODEREF
Brain‑Tumor Diagnostics CNN
MRI classifier for tumor sub‑typing.
CODEREF
Proton Dose 3D Swin‑Transformer
Predicts patient‑specific dose heat‑maps.
CODEREF
Self‑Adapting 3D ViT
Auto‑scales parameters for any modality.
CODEREF
Volumetric GAN (CUDA)
Faster training with custom kernels.
CODEREF
3D Autoencoder (CUDA)
High‑throughput reconstruction.
CODEREF

Papers & Teaching Materials

Lecture Slides: Intro to Medical AI
Master’s course ‑ 120 slides.
SLIDES
Lab Notebook: DL for Computer vision
Hands‑on Colab notebooks.
NOTEBOOKS