Research

Our goal is to study and develop computer algorithms that exhibit human-like cognitive abilities.
Our research focuses on the following areas:

• Machine learning
• Computer vision
• Pattern recognition
• Socio-ethical implications of AI

Our goal is to study the complexity of living systems using a holist approach bridging the borders between Physics, Chemistry, Biology and Medicine. To this aim, we combine computational and experimental tools to find molecular level solutions to a broad range of issues related to medicine, biotechnology, environment and energy.

For a long time, art and science were viewed as distant domains that were only loosely connected, but we’re now witnessing more interaction between the two. This has led to an increased awareness of how art and science are indeed two different but strongly coupled aspects of human creativity, both driving innovation as art influences science and technology, and as science and technology in turn inspire art. This Research Unit will start from these premises to face research challenges at the intersection of art, science, and technology.

Any system in which a large number of elements interact, adapt and evolve to give rise to new meso- and macro-level structures can be described as complex.  Learning about the organization and the dynamic of such systems raise challenging problems with respect to data - how to collect them, how to interpret them, how to use them to build models that can help to predict system dynamics. The RU is devoted to design new methodologies for understanding the fundamental principles of complex systems at a variety of scales, from molecular biology to human societies. Research fields: Adaptive Experimental Design and Clinical Trials, Evolutionary approaches for Multi-Objective Optimization, Intelligent Systems for Data Analysis, Machine Learning, Bayesian Network and Graphs Analysis , Predictive High Dimensional Models, Computational medicine, Econometrics.

The mission of this research unit is to promote the study of the human mind and its social and cultural complexities across major disciplines including neuropsychology, comparative cognitive neuroscience, affective neuroscience and computer science work towards an integrative view of sensory modalities and research methodologies.

The main focus of LT research unit is to develop and explore living technologies, which are technologies that are characterized by robustness, autonomy, energy efficiency, sustainability, intelligence, learning, self-repair, adaptation, self-replication and evolution, all properties most current technologies lack, but living systems possess.

The goal of this research unit is to study and synthesize living and life-like processes, both life-as-we-know-it and life-as-it-could-be regardless of substrate. Substrates can be wet carbon-based chemistry (wet Alife), software-based (soft Alife), robotics-based (hard Alife), or mixtures of these.
Note that living and life-like processes can exist at multiple levels and thus include for example ecological systems and human organizations.

The aim is to study and develop solutions to a variety of complex societal challenges caused by the interactions between technological advancements (‘physical technologies’) on one hand and cultural structures and institutions (‘social technologies’) on the other hand. Such challenges include the erosion of the collective perception of objective facts, increasing inequality, climate change, and loss of biodiversity. There is a sense of urgency to understand the root causes of these disturbing trends and to offer feasible alternative visions of cultural and technological change that can take us in a better direction.