AzadeFarshad

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

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Azade Farshad

Azade

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

  • Phone: +49 (89) 289-19403

* Google ScholarScholar

Research Interests

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

Reviewer

Research Projects

Student Projects

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

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

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

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

Teaching

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)


UsersForm
Title: M.Sc.
Circumference of your head (in cm):  
Firstname: Azade
Middlename:  
Lastname: Farshad
Picture: photo_azade2.JPG
Birthday:  
Nationality: Iran
Languages: English, German, Persian
Groups: Computer Vision, Machine Learning for Medical Applications
Expertise: Computer Vision
Position: Scientific Staff
Status: Active
Emailbefore: azade.farshad
Emailafter: tum.de
Room: MI 03.13.043
Telephone: +49 (89) 289-19403
Alumniactivity:  
Defensedate: 20 April 2018
Thesistitle: Neural Network Compression
Alumnihomepage:  
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