🦕 Donald Shenaj

I am currently doing an internship at Samsung Research UK under the supervision of Umberto Michieli and Mete Ozay.

I hold a Ph.D. in Information Engineering from the University of Padova (Italy), where I was supervised by Prof. Pietro Zanuttigh. From May to November 2023, I was a research intern at Mila - Quebec AI Institute & Concordia University, working with Prof. Eugene Belilovsky.

My research focuses on large-scale machine learning problems and their applications to visual understanding. I have worked on various aspects of Federated Learning, Continual Learning, Domain Adaptation, and Semantic Segmentation. More recently, I have been exploring Model Merging and Image Generation.

[Download CV]

Publications

Preprints

LoRA.rar: Learning to Merge LoRAs via Hypernetworks for Subject-Style Conditioned Image Generation
D. Shenaj, O. Bohdal, M. Ozay, P. Zanuttigh, U. Michieli
arXiv 2024.
[paper][code][video]

Conferences

	Adaptive Local Training in Federated Learning D. Shenaj, E. Belilovsky, P. Zanuttigh International Conference on Learning Representations (ICLR), 2025, MCDC Workshop. [paper]
	When Cars meet Drones: Hyperbolic Federated Learning for Source-Free Domain Adaptation in Adverse Weather G. Rizzoli, M. Caligiuri, D. Shenaj, F. Barbato, P. Zanuttigh IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2025 (oral). [paper][code]
	Source-Free Domain Adaptation for RGB-D Semantic Segmentation with Vision Transformers G. Rizzoli, D. Shenaj, P Zanuttigh IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Pretrain Workshop 2024 (oral). [paper]
	Asynchronous Federated Continual Learning D. Shenaj, M. Toldo, A. Rigon, P. Zanuttigh IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), FedVision Workshop, 2023 (oral). [paper][code]
	Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning D. Shenaj, E. Fanì, M. Toldo, D. Caldarola, A. Tavera, U. Michieli^†, M. Ciccone^†, P. Zanuttigh^†, B. Caputo^† IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023 (oral). [paper][code]

Journals

	Federated Learning in Computer Vision D. Shenaj, G. Rizzoli, P. Zanuttigh IEEE Access, 2023. [paper]
	Continual coarse-to-fine domain adaptation in semantic segmentation D. Shenaj, F. Barbato, U. Michieli, P. Zanuttigh Elsevier Image and Vision Computing, 2022. [paper][webpage][code]

^* Equal contribution. ^† Equal supervision.

Ph.D., Master’s and Bachelor’s Thesis

[T3] D. Shenaj, “Morphing Distributed and Transfer Learning Paradigms for Visual Understanding”, Ph.D thesis in Information Engineering, University of Padova, (Submitted) December 2024.

[T2] D. Shenaj, “Coarse-to-Fine Learning for Semantic Segmentaion across Multiple Domains”, MS thesis in ICT for Internet and Multimedia, University of Padova, September 2021.

[T1] D. Shenaj, “Implementation and analysis of a vehicle counter system with Python and OpenCV”, BS thesis in Electronics Engineering for Energy and Information, University of Bologna, October 2019.