Short Biography

I studied Physics at the Karlsruhe Institute of Technology (2014-2018) and the University of Heidelberg (2018-2021) with the main specific field of Medical Physics. During my Masters in Heidelberg, I worked 2 years as an intern and working student in the field of Deep Learning based Medical Data AI at Mint Medical GmbH. My Master thesis is called "On the impact of auto-generated anatomical context on 2D organ segmentation with Deep Convolutional Neural Networks".

Research Interests

• Deep Learning based Medical Image Segmentation and Classification
• Uncertainty Quantification
• Causal Inference (ML based)

Projects

LeMeDaRT

Teaching

• In preparation

Publications

• S. Machmeier, M. Trageser, M. Buchwald and V. Heuveline, "A Generalizable Approach for Network Flow Image Representation for Deep Learning," 2023 7th Cyber Security in Networking Conference (CSNet), Montreal, QC, Canada, 2023, pp. 57-61, doi: 10.1109/CSNet59123.2023.10339761.
• Marcus Buchwald , Andrei Sirazitdinov , Jürgen Hesser , et al. Review of Deep Learning Methods for Individual Treatment Effect Estimation with Automatic Hyperparameter Optimization. TechRxiv. August 11, 2022.
  DOI: 10.36227/techrxiv.20448768.v1
• A. Sirazitdinov, M. Buchwald, V. Heuveline and J. Hesser, "Graph Neural Networks for Individual Treatment Effect Estimation," in IEEE Access, vol. 12, pp. 106884-106894, 2024, doi: 10.1109/ACCESS.2024.3437665.

Conference Contributions and Talks

• Presentation at the Heidelberg Laureate Forum 2022 for talented young
  researchers around the world - Title: Medical Image Processing
• Supportive speaker of Prof. Jürgen Hesser at the 4EU+ Summer School on
  Artificial Intelligence 2022 in Mailand.

Workshops

• In preparation