Magda Paschali

Magda Paschali PhD Student Email: magda.paschali[@]tum.de Chair for Computer Aided Medical Procedures & Augmented Reality Fakultät für Informatik Technische Universität München Boltzmannstr. 3 85748 Garching b. München Room: MI 03.13.053 Phone: +49 (89) 289-17081 Klinikum Rechts der Isar Interdisziplinäres Forschungslabor Ismaninger Str. 22 81675 München Room: Building 501 - 01.01.3a-c Phone: +49 89 4140 6457 Scholar

Education

• 2017-2021: PhD. Title: Learning Robust Representations for Medical Diagnosis
• 2017: Master of Science in Informatics. Technical University of Munich, Germany
  Thesis: Security of Deep Learning Under Adversarial Settings
  
• 2015: Bachelor in Informatics. Aristotle University of Thessaloniki, Greece
  Thesis: Distance Computation Between Videos Using Dynamic Time Warping

Research Interests

• Machine Learning
• Robustness of Neural Networks
• Federated Learning
• Interpretable Neural Networks
• Medical imaging
  • Whole-Brain Segmentation
  • Ultrasound DeepForming
  • Skin Lesion Classification
  • Medical Image Retrieval

Teaching

• Hauptseminar Deep Learning for Medical Applications (2019WiSe)
• Praktikum Machine Learning in Medical Imaging (2019WiSe)
• Hauptseminar Deep Generative Models (2019SoSe)
• Hauptseminar Deep Generative Models (2018WiSe)
• Hauptseminar Deep Learning for Medical Applications (2018WiSe)
• Praktikum Machine Learning in Medical Imaging (2018WiSe)
• Hauptseminar Deep Generative Models (2018SoSe)
• Hauptseminar Deep Learning for Medical Applications (2018SoSe)
• Praktikum Machine Learning in Medical Imaging (2018SoSe)

List of Preprints and Publications

2020
	H. Hase, MF. Azampour, M. Tirindelli, M. Paschali, W. Simson, E. Fatemizadeh, N. Navab Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning The original manuscript is available currently online on arXiv. (bib)
	T. Czempiel, M. Paschali, M. Keicher, W. Simson, H. Feußner, S.T. Kim, N. Navab TeCNO: Surgical Phase Recognition with Multi-Stage Temporal Convolutional Networks International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI), Lima, Peru, 2020 (The pre-print is available currently online on arXiv) (bib)
	S. Gasperini, M. Paschali, C. Hopke, D. Wittmann, N. Navab Signal Clustering with Class-independent Segmentation 45th International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2020. The original publication is available currently online on arXiv. (bib)
2019
	M. Paschali, F. Naeem, W. Simson, K. Steiger, M. Mollenhauer, N. Navab Deep Learning Under the Microscope: Improving the Interpretability of Medical Imaging Neural Networks The first two authors contributed equally. The original manuscript is available currently online on arXiv. (bib)
	M. Paschali, S. Gasperini, A. Guha Roy, M.Y.-S. Fang, N. Navab 3DQ: Compact Quantized Neural Networks for Volumetric Whole Brain Segmentation The first two authors contributed equally. 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Shenzhen 2019. The original publication is available currently online on arXiv and will become available at link.springer.com (bib)
	M. Paschali, W. Simson, A. Guha Roy, R. Göbl, F. Naeem, C. Wachinger, N. Navab Manifold Exploring Data Augmentation with Geometric Transformations for Increased Performance and Robustness 26th international conference on Information Processing in Medical Imaging (IPMI), Hong Kong 2019. The original publication is available currently online on arXiv and will become available at link.springer.com (bib)
	W. Simson, R. Göbl, M. Paschali, M. Krönke, K. Scheidhauer, S. Weber, N. Navab End-to-End Learning-Based Ultrasound Reconstruction The first two authors contributed equally. The original manuscript is available currently online on arXiv. (bib)
2018
	W. Simson, M. Paschali, N. Navab, G. Zahnd Deep Learning Beamforming for Sub-Sampled Ultrasound Data IEEE International Ultrasonics Symposium (IUS), 2018 Japan (bib)
	M. Paschali, S. Conjeti, F. Navarro, N. Navab Generalizability vs. Robustness of medical imaging networks 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Spain 2018. The original publication is available online at link.springer.com (bib)
	S. Conjeti, M. Paschali, A. Guha Roy, N. Navab Deep Hashing for Large-Scale Medical Image Retrieval Bildverarbeitung für die Medizin 2018 - Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 11. bis 13. März 2018 in Erlangen The original publication is available online at link.springer.com (bib)
2017
	S. Conjeti, M. Paschali, A. Katouzian, N. Navab Deep Multiple Instance Hashing for Scalable Medical Image Retrieval The first two authors contributed equally. 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Canada 2017. The original publication is available online at link.springer.com (bib)

P. Notaro, M. Paschali, C. Hopke, D. Wittmann, N. Navab
Radar Emitter Classification with Attribute-specific Recurrent Neural Networks
arXiv/1911.07683, 2019