Applied research doctoral scholarships: 18 scholarships for innovative PhDs
Technology, Innovation and Management
The projects
• System Identification and Machine Learning for market-oriented eHealth solutions to support clinical decisions, in order to improve diagnostic precision and personalization of treatments
• Artificial Intelligence in the evolution of ecosystems in ProductService System
• Development of 5.0 Skills in the Field of Logistics Supported by Laboratory Teaching Equipment
• Digital sustainability
• Multimedia analysis of online social network contents using Artificial Intelligence
• Study and development of design methodologies for additive manufacturing (DfAM) with optimizations of complex geometries with targets in terms of performance, sustainability and reduction of carbon footprint
• Research, development and tuning of digital and sustainable manufacturing processes using additive deposition of different metallic materials, in wire and powder form, for the production of tailored structures with high performance and low environmental impact
System Identification and Machine Learning for market-oriented eHealth solutions to support clinical decisions, in order to improve diagnostic precision and personalization of treatments
Affiliated company: Net-Medicare SRL
Supervisor: Prof. Fabio Previdi, University of Bergamo
In the evolving field of digital medicine, advanced eHealth solutions are essential for supporting clinical decision-making, enhancing diagnostic accuracy and enabling personalized treatments. This research project aims to develop such solutions by integrating System Identification technologies such as predictive maintenance, adaptive systems and realtime monitoring. The goal of the project is to create marketable models of patient health dynamics to support the development of predictive algorithms. These algorithms, trained through Machine Learning, will identify patterns in patient data, improving diagnostic precision. Furthermore, the project will implement adaptive learning systems that update continuously based on new patient data, customizing treatment plans in real-time. The project’s focus on personalized medicine will revolutionize how treatments are tailored to individual patients and test its findings in real-life applications.
By leveraging predictive algorithms and adaptive learning systems, healthcare providers will be able to develop treatment plans that are specifically designed to meet the unique needs of each patient. Additionally, the use of real-time monitoring technologies will allow for the continuous collection of Electronic Health Record data of patients affected by chronic diseases, enabling healthcare providers to make timely adjustments to treatment plans for continuous care.
The project will be based on a dynamic and practical approach ensuring that each patient can receive the most appropriate and effective care, improving overall health outcomes and patient satisfaction, and orienting the created solutions towards business realities on the market. By bridging the gap between innovative research and commercial needs, the release of scalable eHealth solutions will significantly enhance patient care.
Artificial Intelligence in the evolution of ecosystems in Product-Service System
Affiliated
company:
Supervisors:
Consorzio Intellimech
Prof. Fabiana Pirola, Prof. Giuditta Pezzotta, University of Bergamo
Manufacturing companies are increasingly expanding their product offerings with value-added services for their customers, with the aim, on the one hand, of obtaining economic benefits and, on the other, of reducing environmental impact by extending product life cycles.
At the same time, the evolution of technology and, in particular, of Artificial Intelligence (AI), is allowing to improving the service offered, thanks to the potential for data and text analysis, and prediction.
The PhD project, carried out in collaboration with Intellimech, a private non-profit research consortium that promotes collaboration between companies of different sizes and from various industrial sectors, aims to analyze the impact of AI in the product-service offering as well as its effect on the relations between the stakeholders of the ecosystem.
Thus, starting from an analysis of the state of the art and the needs of companies, the project envisages the identification of (i) the potential offered by AI in the service offering, in terms of both applications and technologies; (ii) the barriers to its adoption; and (iii) the organizational changes required for its implementation, both in terms of the product and the service delivery processes.
The final step of the project is the development a product-service solution enabled by AI in a business case.
Development of 5.0 Skills in the Field of Logistics
Supported by Laboratory Teaching Equipment
Affiliated company: Fondazione ITS Mobilità Sostenibile - Mobilità delle persone e delle merci
Supervisors: Prof. Alexandra Lagorio, Prof. Roberto Pinto, University of Bergamo
The increase in urban population, digitalization, workforce aging, the e-commerce boom, challenges from the need for increasingly resilient supply chains, and an ever-increasing focus on ecological transition and sustainability issues represent major challenges for companies in the logistics sector.
Facing these challenges through 5.0 logistics (digital, human-centric, resilient, and sustainable) implies the need for new skills in the logistics world, which are not always easy to find locally.
The lack of resources with adequate skills (skill shortage) subsequently necessitates the development of innovative training programs for various interested targets (university students, ITS students, master’s students, workers, and elderly workers).
This doctoral project has the dual objective of:
• investigating the new skills required by Logistics 5.0;
• understanding the paths, methods, and tools that can be developed depending on the different targets and educational objectives.
The research project involves developing methods and paths for training, starting from an analysis of the role of technologies in supporting logistics workers and the impacts they have on the main activities to be carried out and on job profiles.
These analyses will be developed through the collaboration of a network of laboratories where learning factories and industrial technologies applicable in the field of logistics are installed.
Digital sustainability
Affiliated company: Warrant Hub Spa Supervisor: Prof. Davide Russo, University of Bergamo
The advent of new Artificial Intelligence tools is revolutionising the way companies approach sustainability-related activities such as LCA reporting, criticality analysis and green improvement activities.
In this project, it is interesting to delve into sustainability-related R&D activities, which usually require a great deal of time and resources.
The primary objective of this project is to build AI-based infrastructures that can be integrated with new knowledge bases to create a new generation of tools to support design for sustainability.
Thanks to this combination, it will be possible to quickly analyse huge volumes of data, develop data-driven eco-design strategies, circularity paths for production waste, new second-life scenarios for products, automate the collection of information for LCA, carbon footprint or ESG, facilitate the drafting of technical reports, EPDs, LCAs and identify prospective LCA trends.
Multimedia analysis of online social network contents using Artificial Intelligence
Affiliated company: CINI - Consorzio Interuniversitario Nazionale per l’Informatica
Supervisor: Prof. Vincenzo Moscato, University of Naples “Federico II”
The research project focuses on the multimedia analysis of online social network contents using Artificial Intelligence techniques.
The goal is to develop and apply advanced algorithms to understand, classify, and interpret texts, images, and videos on social media.
Through these analyses, the project aims to enhance the understanding of social dynamics, online interactions, and emerging trends on the basis of models capable of taking into account multimedia content.
Additionally, it seeks to identify patterns of behavior, cultural influences, and potential risks associated with the spread of false or misleading information which can support the current Social Network Analysis applications.
Study and development of design methodologies for additive manufacturing (DfAM) with optimizations of complex geometries with targets in terms of performance, sustainability and reduction of carbon footprint
Affiliated company: 3 DnA Srl
Supervisors: Prof. Antonio Lanzotti, Prof. Massimo Martorelli, University of Naples “Federico II”
This research aims at providing a further insight in the design and development of advanced and lightweight additive manufactured devices as well as of innovative/integrated technological solutions in the industrial field.
Research, development and tuning of digital and sustainable manufacturing processes using additive deposition of different metallic materials, in wire and powder form, for the production of tailored structures with high performance and low environmental impact
Affiliated company: 3 DnA Srl
Supervisor: Prof. Antonio Squillace, University of Naples “Federico II”
The proposed research project aims to research, develop and fine-tune digital and sustainable manufacturing processes using additive deposition of different metals, even different alloys, in wire (Wire Arc Additive Manufacturing via Cold Metal Transfer) and powder form (Selective Laser Melting). The goal is to produce tailored structures with high performance and low environmental impact for advanced industrial applications.
