I’m passionate about Artificial Intelligence and its impact on how we interact with the world around us. My background in Computer Engineering and AI led me to pursue a PhD at MICC in Florence, Italy, under the esteemed supervision of Prof. Andrew D. Bagdanov. Now I’m diving deep into the world of Multimodal Vision-Language Models and their applications in solving real-world challenges.

I'm really into:

• 🧠 Multimodal Learning: Combining visual and language data to get a richer understanding of the world.
• 💬 Natural Language Processing (NLP): Teaching machines to understand and communicate in human language.
• 🖼️ Contrastive Self-Supervised Learning: Finding patterns in data without the need for human labels.
• ♻️ Incremental Learning: Allowing AI models to keep learning from new information without forgetting the old ones.
• 🎯 Few-Shot Adaptation: Quickly adapting AI to a diverse data distribution with minimal examples.
• 📝 Prompt Learning: Tuning only a few learnable parameters, so-called "prompts", to maximize VLMs performance.
• 🚀 Test-Time Adaptation: Letting models adjust during inference to handle unseen data on the fly.

• Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation – Published at ECCV 2024, co-authored with Alberto Baldrati, Marco Bertini, and Andrew D. Bagdanov.

• Programming Languages: Python, Java, C++, MATLAB, R
• Frameworks & Tools: PyTorch, TensorFlow, Hugging Face, OpenCV
• Research Areas: Vision-Language Models, Self-Supervised Learning, Few-Shot Learning, Prompt Learning, Incremental Learning

I’d love to connect! Feel free to reach out on: