Mischa Dombrowski

Mischa Dombrowski

PhD Student & Director of IT @ IDEA Lab
Werner-von-Siemens Str. 61
91052 Erlangen

  • Jan. 2022 – now
    Ph.D., Friedrich-Alexander-Universität Erlangen-Nürnberg,
    Department for Artificial Intelligence in Biomedical Engineering,
    Intelligent Data Exploration and Analytics (IDEA) Lab
  • Jan. 2021 – Dez. 2021
    Student Assistant,
    Department for Artificial Intelligence in Biomedical Engineering,
    Machine Learning and Data Analytics Lab
  • Oct. 2019 – Nov. 2021
    M.Sc. Information and Communication Technology,
    Friedrich-Alexander-Universität Erlangen-Nürnberg,
    Faculty of Engineering
  • Oct. 2016 – Sep. 2019
    B.Sc. Informations und Kommunikationstechnologie,
    Friedrich-Alexander-Universität Erlangen-Nürnberg,
    Faculty of Engineering

  • Dombrowski, M. and Kainz, B., (2023). Quantifying Sample Anonymity in Score-Based Generative Models with Adversarial Fingerprinting. arXiv preprint arXiv:2306.01363.
  • Reynaud, H., Qiao, M., Dombrowski, M., Day, T., Razavi, R., Gomez, A., Leeson, P. and Kainz, B. (2023). Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis. arXiv preprint arXiv:2303.12644.
  • Baugh, M., Tan, J., Müller, J. P., Dombrowski, M., Batten, J., & Kainz, B. (2023). Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks. arXiv preprint arXiv:2307.00899.
  • Dombrowski, M., Reynaud, H., Müller, J. P., Baugh, M., & Kainz, B. (2023). Pay Attention: Accuracy Versus Interpretability Trade-off in Fine-tuned Diffusion Models. arXiv preprint arXiv:2303.17908.
  • Müller, J. P., Baugh, M., Tan, J., Dombrowski, M., & Kainz, B. (2023). Confidence-Aware and Self-Supervised Image Anomaly Localisation. arXiv preprint arXiv:2303.13227.
  • Dombrowski, M., Reynaud, H., Baugh, M., Kainz, B. (2022). Foreground-Background Separation through Concept Distillation from Generative Image Foundation Models
  • Reynaud, H., Vlontzos, A., Dombrowski, M., Gilligan Lee, C., Beqiri, A., Leeson, P. and Kainz, B., (2022). D’artagnan: Counterfactual video generation. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 599-609). Cham: Springer Nature Switzerland.

  • Project: Representation Learning
  • Exercise Medical Engineering II
  • Exercise Algorithms, programming, and data representation