Recently the Technology Transfer (TT) issue is becoming more and more relevant for business economies and strategic for the development of countries. TT refers to the transformation process which, starting from the results of scientific and technological research, produces solutions ready for the market and society, together with the associated skills and procedures. TT is therefore a fundamental part of the technological innovation process which involves several activities.
Unfortunately, the very rapid evolution of scientific and technological research produces an impressive amount of results with great speed, which the traditional TT process is not able to process adequately. In order to exploit the enormous potential of results made available recently by scientific and technological research, a more effective and efficient TT is necessary.
Artificial Intelligence (AI) offer a great potential to optimizing TT processes with respect to different domains and specific application needs.
This workshop aims to foster the most advanced research on innovative techniques and intelligenet systems for TT, based on the use of data-driven along with AI/ML approaches.
List of topics of interest:
Topics of interest include (but are not limited to):
- Databases Development for TT
- Data Driven TT
- Digital Twin of TT
- Digitalization of TT Processes
- Intellectual Property Analytics
- Knowledge management for TT processes
- Leveraging ML/AI for TT processes framing and optimisation
- Patent Mining
- TT Modelling
- Giuseppe Pirlo, Dipartimento di Informatica, Università degli Studi di Bari, Italy,
- Mohamed Cheriet, Department of System Engineering, University of Quebec's Ecole de technologie supérieure (ETS), Montreal (Quebec), Canada,
Program Committee (Names and affiliations) (TBC):