Key Contributor to Google's Gemini Models

Played a pivotal role in the research, development, and scaling of Google's next-generation multimodal AI models, Gemini, contributing to its core capabilities, training methodologies, and safety protocols.

PhD in Computer Science from Imperial College London

Successfully completed doctoral research at Imperial College London, one of the world's leading universities, focusing on advanced machine learning techniques and their applications, which has significantly informed his work in AI.

Advancements in Responsible AI and Model Safety

Actively contributes to research and implementation of state-of-the-art techniques for ensuring the safety, fairness, and ethical considerations in the deployment of large-scale AI models at Google.

Thought Leadership in AI

Frequently shares insights and research findings through publications, technical talks, and articles, contributing to the broader AI community's understanding of LLMs and generative AI. (Note: Specific publications can be found on Google Scholar or his Google Research page).

Innovations in Efficient AI Model Training

Contributed to developing and implementing novel techniques for more efficient training and inference of large-scale neural networks, enabling the creation of more powerful and accessible AI models.

Diploma Istituto Tecnico e Professionale, Ragioniere con spec. Programmazione Elettronica

ITC "P. Verri" Milano - Year 1974

Università Cattolica del Sacro Cuore