Donald Shenaj | Ph.D. Student

Phone (office): +39 049 827 7774


Donald Shenaj is a PhD StudentĀ at the Department of Information Engineering of the University of Padova. He received the Bachelor’s Degree in Electronics Engineering at University of Bologna in October 2019, and the Master’s Degree in ICT for Internet and Multimedia at University of Padova in September 2021, both with honors. Currently, he is a visiting researcher at Mila – Quebec Artificial Intelligence Institute in Montreal, Canada. He is interested in large scale machine learning problems and their applications to computer vision.


Research areas

Federated Learning

Federated learning is a decentralized machine learning approach that allows multiple devices to train a shared model collaboratively while keeping their local data private.

Continual Learning

Continual learning refers to the ability of a machine learning model to continuously acquire and retain knowledge from new data while retaining previously learned information. 

Domain Adaptation

Domain Adaptation aligns a network from a source dataset to perform on a target dataset with a different distribution. Complex neural networks require abundant labeled data, which limits their application in many real-world scenarios.



Shenaj, Donald; Toldo, Marco; Rigon, Alberto; Zanuttigh, Pietro

Asynchronous Federated Continual Learning Proceedings Article

In: CVPR FedVision Workshop, 2023.


Shenaj, Donald; Fan`i, Eros; Toldo, Marco; Caldarola, Debora; Tavera, Antonio; Michieli, Umberto; Ciccone, Marco; Zanuttigh, Pietro; Caputo, Barbara

Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning Proceedings Article

In: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2023, 2023.


Shenaj, Donald; Rizzoli, Giulia; Zanuttigh, Pietro

Federated Learning in Computer Vision Journal Article

In: IEEE Access, 2023.



Shenaj, Donald; Barbato, Francesco; Michieli, Umberto; Zanuttigh, Pietro

Continual coarse-to-fine domain adaptation in semantic segmentation Journal Article

In: Image and Vision Computing, vol. 121, pp. 104426, 2022.

Links | BibTeX