Azade Farshad

Azade Farshad PhD Candidate * Email: azade.farshad[at]tum.de * Address: Chair for Computer Aided Medical Procedures & Augmented Reality Fakultät für Informatik Technische Universität München Boltzmannstr. 3 85748 Garching b. München Room: MI 03.13.043 Phone: +49 (89) 289-19403 * Scholar

Research Interests

• Unsupervised Learning
  
• Self-Supervised Learning
  
• Meta-learning
  
• Scene graphs
  
• Generative Models
• Optimization

Reviewer

• International Conference on Learning Representations (ICLR), Virtual, 2022
• Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA 2022
• British Machine Vision Conference (BMVC), Virtual, UK 2021
• International Conference on Computer Vision (ICCV), Montreal, Canada 2021
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, USA 2021
• Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, USA 2021
• Asian Conference on Computer Vision (ACCV), Kyoto, Japan 2020
• British Machine Vision Conference (BMVC), Manchester, UK 2020
• European Conference on Computer Vision (ECCV), Glasgow, Scotland 2020
• IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, USA 2020
• British Machine Vision Conference (BMVC), Cardiff, UK 2019

Research Projects

• Semantic Image Manipulation using Scene Graphs Project Page | Code
• Neural Network Compression Project Page

Student Projects

Feel free to contact me for any of the following projects.

Available
Project	Meta-Optimization (Azade Farshad, Prof. Dr. Nassir Navab)

Running
Master Thesis	Self-Supervised Generative Modelling for Contrastive Learning (Azade Farshad, Prof. Dr. Nassir Navab)

Finished
Master Thesis	Scene graph generation (Helisa Dhamo Azade Farshad, Federico Tombari)
Master Thesis	Meta-learning for Image Generation/Manipulation using Scene Graphs (Azade Farshad, Helisa Dhamo, Prof. Dr. Nassir Navab)
Project	Meta-learning for Medical Image Segmentation (Azade Farshad, Prof. Dr. Nassir Navab)
Master Thesis	Meta-clustering (Azade Farshad, Prof. Dr. Nassir Navab)
Master Thesis	Towards More Robust Machine Learning Models (Azade Farshad, Dr. Alexander Urich, Prof. Dr. Nassir Navab)
Master Thesis	Federated Learning with Non-iid data (Dr. Shadi Albarqouni, Azade Farshad, Prof. Dr. Nassir Navab)
Project	Robustness of Knowledge Transfer Methods (Dr. Shadi Albarqouni, Azade Farshad, Prof. Dr. Nassir Navab)

Teaching

• Hauptseminar Deep Learning for Medical Applications (2021WiSe)
• Praktikum Machine Learning in Medical Imaging (2021WiSe)
• Hauptseminar Deep Learning for Medical Applications (2021SoSe)
• Praktikum Machine Learning in Medical Imaging (2021SoSe)
• Hauptseminar Deep Learning for Medical Applications (2020WiSe)
• Praktikum Machine Learning in Medical Imaging (2020WiSe)
• Hauptseminar Deep Learning for Medical Applications (2020SoSe)
• Praktikum Machine Learning in Medical Imaging (2020SoSe)
• Praktikum Machine Learning in Medical Imaging (2019WiSe)
• Hauptseminar Deep Generative Models (2019SoSe)

• Hauptseminar Computer Vision and Deep Learning for Autonomous Driving (2020WiSe)
• Hauptseminar Deep Learning for Medical Applications (2019WiSe)
• Praktikum Machine Learning in Medical Imaging (2019SoSe)
• Hauptseminar Deep Generative Models (2018WiSe)

List of Publications

2021
	S. Garg, H. Dhamo, A. Farshad, S. Musatian, N. Navab, F. Tombari Unconditional Scene Graph Generation IEEE International Conference on Computer Vision (ICCV), October 2021 The first two authors contributed equally. (bib)
2020
	H. Dhamo, A. Farshad, I. Laina, N. Navab, G. D. Hager, F. Tombari, C. Rupprecht Semantic Image Manipulation Using Scene Graphs IEEE Computer Vision and Pattern Recognition (CVPR), Seattle, WA, USA, June 2020 The first two authors contributed equally. (bib)
	Y. Yeganeh, A. Farshad, N. Navab, S. Albarqouni Inverse Distance Aggregation for Federated Learning with Non-IID Data MICCAI Workshops proceedings with Springer (LNCS) (bib)
2018
	V. Belagiannis, A. Farshad, F. Galasso Adversarial Network Compression ECCV 2018 Workshops. ECCV 2018. Lecture Notes in Computer Science, vol 11132. Springer, Cham (bib)