Scholar
Vincenzo Lomonaco
Google Scholar ID: rQLINtQAAAAJ
Associate Professor @ LUISS | Co-Founder @ ContinualAI.org & ContinualIST.ai
Citations & Impact
Citations
4,293
H-index
27
i10-index
44
Publications
20
Co-authors
174
list available
Publications
Resume (English only)
Academic Achievements
- Secured over €2 million in funding within six years of post-PhD research, including the prestigious Italian Science Fund (FIS) – Starting Grant, a PRIN, and collaborations with international organizations such as Intel, Meta, Leonardo, and ESA. Published more than 80 scientific papers in top-tier conferences and journals on the topic of Sustainable Artificial Intelligence. Received the “Marco Somalvico” Award 2025 from the Italian Association for Artificial Intelligence. Notable research milestones include: 1st PhD dissertation on Deep Continual Learning; organizing the 1st Continual Learning in Computer Vision workshop at CVPR 2020; releasing Avalanche: the reference open-source library for Continual Learning (winner of the W&B Best Library award); authoring the reference open-access course on Continual Learning (430+ students from 300+ institutions, 5k+ YouTube views). Recent publications include [Paper] Continual Learning: Applications and the Road Forward, [Paper] Design Principles for Lifelong Learning AI Accelerators published in Nature Electronics!
Research Experience
- Currently an Associate Professor at the Department of AI, Data and Decision Sciences at Luiss Guido Carli University, leading the Collage Lab. Co-founder of ContinualIST, a spin-off of the University of Pisa; Founding member of the non-profit organization ContinualAI; Principal Investigator in several research projects and industrial collaborations.
Education
- PhD: 2019, University of Bologna, Advisor: Davide Maltoni, Dissertation: “Continual Learning with Deep Architectures”, recognized as one of the top-5 AI dissertations of 2019 by the Italian Association for Artificial Intelligence.
Background
- Main research interest: Sustainable Artificial Intelligence, particularly through the lenses of Deep Learning, focusing on Continual Learning, Decentralized Learning, and Multi-Agent Interaction towards a greener and more democratic AI development.
Miscellany
- No personal interests mentioned.
