Ahmad Hassanpour

A Postdoctoral Researcher focuses on securing agent-based AI models for healthcare applications. From Jan. 2021 till Sep. 2024, I was a Marie Curie fellow in the framework of Marie Curie ITN Privacy Matters (PriMa) project and a Ph.D. candidate at Norwegian University of Science and Technology (NTNU), mainly working on privacy and machine learning paradigms.

Current Primary Interests

Preserving privacy in deep learning algorithms
Differential privacy
Federated learning

Updates

Nov, 2023: One paper accepted in ASONAM 2023. The 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Sep, 2023: Accepted paper at IEEE International Joint Conference on Biometrics (IJCB 2023). paper
Aug, 2023: Our team has achieved the second and third ranks in the Efficient Face Recognition Competition (EFaR-2023). paper
Aug, 2023: One paper accepted in IEEE Access. paper
Oct, 2022: I will start an internship at SAP company working on preserving fairness and privacy in machine learning models.
Sep, 2022: One paper accepted in ASONAM 2022. The 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Sep, 2022: Speaker at EAB-RPC 2022, Germany. EAB Research Projects Conference 2022
Aug, 2022: Reviewer for ICMLA2022, The Bahamas. Conference Webpage
June, 2022: Presenting my recent works at UAM university, Madrid.
Mar, 2022: One paper accepted in IEEE Access
Feb, 2022: One paper accepted in IEEE Access
Nov, 2021-Feb, 2022: Visiting researcher at Biometrics and Data Pattern Analytics (BiDA) lab UAM university, Madrid.

Publications

E2F-GAN: Eyes-to-Face Inpainting via Edge-Aware Coarse-to-Fine GANs

Ahmad Hassanpour, Amir Etefaghi Daryani, Mahdieh Mirmahdi, Kiran Raja, Bian Yang, Christoph Busch, Julian Fierrez

IEEE Access 10 (2022): 32406-32417

[IEEE Access]

Differential Privacy Preservation in Robust Continual Learning

Ahmad Hassanpour, Majid Moradikia, Bian Yang, Ahmed Abdelhadi, Christoph Busch, Julian Fierrez

IEEE Access 10 (2022): 24273-24287

[IEEE Access]

Software defect prediction based on deep learning models: Performance study

Ahmad Hassanpour, Pourya Farzi, Ali Tehrani, Reza Akbari

arXiv preprint, (2020)

[arXiv:2004.02589]

A novel end-to-end deep learning scheme for classifying multi-class motor imagery electroencephalography signals

Ahmad Hassanpour, Majid Moradikia, Hojjat Adeli, Seyed Raouf Khayami, Pirooz Shamsinejadbabaki

Expert Systems, 36(6) (2019), p.e12494

[Expert Systems]