About me
Deep learning and 3D computer vision researcher, currently focused on healthcare applications.
Over the past several years, I’ve developed large-scale transformer-based and convolutional architectures for diverse medical modalities (CT, MRI, 3D point clouds) and tasks (segmentation, landmarking, generative AI), with research published at top-tier conferences including CVPR, ICCVW, and 3DV.
I’m motivated by complex research challenges and the opportunity to bridge innovative AI methods with real-world applications, developing solutions that can make a meaningful impact on society.
Download my CV
Interests
- 3D Vision (Images, Point Clouds)
- Deep Learning (Transformers, CNNs)
- Generative Diffusion Models
- Medical Imaging
- Semantic Segmentation
- Python (PyTorch, DDP)
- Scalable Training on HPC
Education
- PhD Deep Learning and 3D Vision in Healthcare, 2025
Mines Paris - PSL Univeristy, France - MSc in ICT for Internet and Multimedia cum laude, 2021
Università degli Studi di Padova, Italy - MSc in Telecommunication Engineering, 2021
Universidad Politecnica de Madrid, Spain - BSc in Information Engineering, 2018
Università degli Studi di Padova, Italy
Recent Updates
- Jan. 13, 2026 "LmPT: Conditional Point Transformer for Anatomical Landmark Detection on 3D Point Clouds" is accepted by ISBI'26
- Dec. 19, 2025 PhD received from Mines Paris - PSL
- Dec. 2025 Landmarks Point Transformer (LmPT) architecture now available . More details here.
- Nov. 05, 2025 "Rethinking Metrics and Diffusion Architecture for 3D Point Cloud Generation" is accepted by 3DV'26 . More details here.
- June 2025 Diffusion Point Transformer (DiPT) architecture releasing soon
- Feb. 26, 2024 Coupled Laplacian is accepted by CVPR'24 . More details here.