Research & Initiatives

Research in Innovation Engineering

Innovation Engineering is dealing with methods, methodologies and technologies for developing mature solutions to technology and business problems and barriers for companies and organizations, including the adoption of emerging technologies (e.g. big data, data science, deep learning, blockchain, IoT, robotics), technology-driven business models, new forms of organizational culture, etc.

Science and Engineering of Artificial Intelligence in Robotic Systems

Science of Interdisciplinary Design for Breakthrough Innovations

Innovation for X

Artificial Intelligence (AI) is the term used for a set of methods, approaches and algorithms inspired from the behavior of living systems (including humans) for solving complex problems. In the field robotic systems we meet the following sub-fields of AI: deep learning, machine learning, swarm intelligence, genetic and other evolutionary algorithms, natural language processing, feature recognition by vision systems with feedback loops, navigation algorithms based on sensing systems and self-decision mechanisms, fuzzy logic, expert systems, ontologies, speech-to-behavior, as well as many other approaches that relate to collaborative artificial systems (negotiation, socialization, collective optimization, self-optimization, autonomy, etc.).
Interdisciplinary Design is about integration of knowledge and practices from more disciplines in order to tackle complex problems and to benefit from the collaboration of experts with complementary and cross-disciplinary backgrounds. Its philosophy is based on the idea that exceptional results are direct proportional with the creative potential, expertise, methods and technologies used to solve a certain problem. To set up an interdisciplinary design team is not just putting together people with different backgrounds. It is about the capacity to put them to cooperate under the guidance of systematic roadmaps and with the proper integration of heterogeneous design tools.
Innovation for X is about directing innovation towards one or more objective-functions. For example, innovation for reconfiguration or innovation for disruption are both related to innovation for X. Green design, blue design are other examples. Each objective function has unique challenges and requires specialized tools and approaches. Some objective-functions that will shape our future are: agility, resilience, circularity, servitization, digitalization, intelligence, autonomy, regeneration, mass customization, personalization, life-cycle approach, etc.

Research in Innovation Management

Innovation Management is about all processes and related activities needed to introduce innovation within a system, which in practice means things like coming up with ideas, developing, prioritizing and implementing them, as well as putting them into practice, by launching new products or services, as well as by introducing new internal processes, new business models, new marketing practices, new forms of collaboration and partnerships, etc.

Science of Smart Innovation and Innovation Systems

Science of Collaborative Innovation

Innovation by Structural Transformation

Smart Innovation is a complex of interventions at system level (organization, sector, cluster, region) that produces positive effects (e.g. sustainable growth, by activating and organizing in a smart way areas with passive endowments, as well as valorising passive evolutionary resources and new unveiled resources. Smart innovation should release cost-effective solutions to a problem, avoiding in the same time the generation of harmful side effects. It comprises the study of micro, mezzo and macro innovation systems, too.
Collaborative Innovation is a process in which multiple players contribute towards creating and developing new products, services, policies, processes, or business solutions, as well as generation of new value chains and new business ecosystems. Collaborative innovation includes several paradigms, such as Innovation 2.0 up to Innovation 5.0. Innovation 2.0 is also called open innovation, and it involves all stakeholders to work together in order to co-create the future and drive structural changes far beyond the scope of what any one organization or person could do alone. Innovation 3.0 is also called distributed open innovation, and it involves modernization, poly-centrism, and strategic alignment of clusters. Innovation 4.0 is about transformation and collaboration in extended open networks, and it involves cross-cluster collaboration and open platforms. Innovation 5.0 is about metamorphosis, where advanced concepts are embedded, such as fast reconfiguration, agile and dynamic forms of joint ventures by aggregating "holons" of resources from various competent systems (community, platforms, government, firms, etc.) that agree upon a common innovation plan and value-driven rules of management and benefit distribution. It requires extensive digitalization and connectivity to global resources.
Innovation by Structural Transformation is about the specialization of innovation and specialized innovation policies that focus on own competitive advantages to produce differentiation and "blue ocean" spaces for sustainable growth. Digital transformation, green-economy or blue-economy driven businesses are also related to structural transformation of organizations or business ecosystems.