
Filippo Chiarello is an Associate Professor of Design and Innovation at the School of Engineering, University of Pisa. His research explores how Generative AI, Natural Language Processing and data-driven methods can be used to study technological innovation, engineering design and organisational phenomena. His work connects artificial intelligence, innovation management and sustainability, with a particular focus on extracting knowledge from textual data, analysing emerging technologies and understanding the impact of AI on skills, education and new product development.
At the University of Pisa, he also contributes to faculty development and holds institutional responsibilities within the Teaching and Learning Centre. He coordinates the DETAILLs research group, a living lab dedicated to the use of Artificial Intelligence and Generative AI for sustainable product design, responsible innovation, and collaboration among universities, students, and companies. His recent publications address topics such as large language models in engineering design, AI for innovation management, text mining for sustainability and the role of Generative AI in education and human skills.
- Institute for Manufacturing
- 17 Charles Babbage Road
- Cambridge CB3 0FS
Research
- Artificial Intelligence
- Asset Management
- Business Model Innovation
- Computer Aided Manufacturing
- Decision-Making for Emerging Technologies
- Design Management
- Digital Manufacturing
- Distributed Information & Automation Laboratory
- Ecosystems, Platforms & Strategy
- Fluids in Advanced Manufacturing
- Healthcare
- Industrial Photonics
- Industrial Resilience
- Industrial Sustainability
- Inkjet Research
- Innovation and Intellectual Property
- International Manufacturing
- Manufacturing Industry Education Research
- NanoManufacturing
- Nexus of Energy and Water Processes
- Science, Technology & Innovation Policy
- Strategy and Performance
- Technology Enterprise
- Technology Management
- Service Alliance
- University Commercialisation and Innovation Policy Evidence Unit








