Davide Rigoni, Ph.D.
I am Davide, a postdoctoral researcher at the University of Padova, Italy. I am an active member of the MMS and MLG groups, focusing my research on the applications of machine learning under the supervision of Stefano Moro and Alessandro Sperduti. My interests include exploring deep generative models in the domain of new drug and material generation and investigating deep learning models for visual-textual grounding.
I earned my Ph.D. in Brain, Mind, and Computer Science from the University of Padova in collaboration with Fondazione Bruno Kessler. Throughout my doctoral program, I conducted research both at the University of Padova in the MLG group under the supervision of Alessandro Sperduti, and Fondazione Bruno Kessler in the DKM group under the supervision of Luciano Serafini. I conducted a research period at the University of Copenhagen under the supervision of Desmond Elliott. Previously, I received my bachelor's and master's degrees from the School of Computer Science at the University of Padova. During my bachelor's studies, I also had the opportunity to participate in the Erasmus program at the Universitat Autònoma de Barcelona.
NEWS
[02/2024] New preprint: Rigoni, Davide, et al. "TumFlow: An AI Model for Predicting New Anticancer Molecules." bioRxiv (2024): 2024-02.
[01/2024] A Gradio custom object displaying a gallery of 2D molecular structures. [GitHub][pip][DEMO]
[01/2024] A Gradio custom object displaying a gallery of interactive 3D molecular structures. [GitHub][pip][DEMO]
[01/2024] Special Session Deep Learning for Graphs accepted at the 2024 IEEE International Joint Conference on Neural Networks, World Congress on Computational Intelligence (WCCI), which will be held in Yokohama, Japan, June 30 - July 5, 2024.
[09/2023] Ph.D. thesis online: Rigoni, Davide. "Understanding Multimedia Content with Prior Knowledge." Università degli studi di Padova (2023).
[09/2023] Paper accepted at BMVC 2023: Rigoni, Davide, et al. "Weakly-Supervised Visual-Textual Grounding with Semantic Prior Refinement." arXiv preprint arXiv:2305.10913 (2023).