The course aims to provide an in-depth understanding of digital innovation and technology transfer,
focusing on risk assessment, climate change, artificial intelligence, and biomedical applications. It
will analyze digital innovations in climate change, risk assessment, and biomedical diagnostics,
with particular attention to AI techniques. Additionally, the course introduces innovation processes
from research to market, analyzing practical cases and criteria for selecting research outcomes for
practical applications.
There are no strictly mandatory prerequisites for students.
A basic understanding of the concepts of innovation, especially in the technological field, and knowledge transfer, as well as intellectual property (e.g. patents and trademarks), can be useful to address issues related to innovation management.
A basic knowledge of the concepts and techniques of risk assessment and artificial intelligence can also be useful.
Finally, students will be asked to present a project on their own business idea-technology transfer, so it is useful to have good communication skills, both written and oral, to prepare and present reports and projects effectively.
The course involves active student participation. There will be lectures and interactive labs for
implementing the final project.
To receive credit recognition, attendance of at least 75% of the scheduled hours is required. A
project presentation will be required and evaluated at the end of the course, including potential
questions on the topics covered.
The course will examine digital innovations in climate change, risk assessment, medical diagnostics
with AI, and cultural heritage. Students will learn to define and differentiate concepts of risk and
damage, using qualitative and quantitative approaches, and exploring strategies for adaptation and
mitigation. European regulations on technology transfer and the management of industrial property,
including patents and trademarks, will be examined. The course will also cover topics related to
startups and spin-offs, teaching students how to develop business plans and analyze competitors.
Case studies such as "Mate" for climate change and "DeepTrace" for AI diagnostics will illustrate
practical applications. The course concludes with the preparation and presentation of a final project
on a technology transfer entrepreneurial idea, integrating all acquired knowledge.
Part of the course material will be made available at the end of the lectures.
