Invited Talks

PolySense: Sustainable Intelligence


"Nothing is permanent, except change" Aristotles. The last months, our lives are changing at a tremendous pace. This change is powered by different seismic shocks like the biological shock of 2020, ecological shocks, geopolitical shocks and socials shocks. This world full of uncertainties is called "the never normal" by Peter Hinssen. It is time to collaborate with new technologies, such as artificial intelligence, to speed up our understanding and make the right decisions in this never normal world. But how do we find the right balance? Current AI use cases surely have an indirect positive impact when it gets to sustainability, but today they do this at an ever increasing direct negative impact on the planet from a CO2 emission perspective. Realising net positive intelligence, by creating AI solutions that exhibit a sustainable goal with an optimised energy efficiency setup, will be key in the future. Learn more about these concepts during my talk at SCIFI-IT 2023.

Short Biography

to be added

Yarne De Munck
Ghent, Belgium

QFVSOOM a Quantum Object-Oriented Model Based on Temporal Fuzzy Vector Spaces that unifies the Microscopic and Macroscopic Levels of Quantic Mechanics


The QFVSOOM is an extension of the Fuzzy Vector Space Object Oriented (FVSOOM) model which revisits the theory of quantum mechanics of Schrödinger and offers a solution to implement the arrow of time and the irreversibility of complex systems as proposed by Ilya Prigogine in his book «La fin des certitudes». Our approach is compatible with thermodynamics and explains that at each level of the hierarchy of composition objects occur interactions and interferences over time that are responsible for the emergence of new properties. The bifurcations linked to these interferences produce at every moment the irreversibility of the system contrary to the classical mechanics of Newton and the quantum mechanics of Schrödinger which are reversible. Like Ilya Prigogine, we believe in a probabilistic evolution of the bifurcations of the system’s components over time. QFVSOOM provides temporal modeling of the evolution of component objects and junction objects, with system states using Dynamic Finite State Automata (DFSA) which generalize the proposed FVSOOM model and Markov chains and that provides a programmable solution to the systemic specifications of quantum mechanics. We will show that our model is applicable not only to the microscopic level of physics and chemistry, but in turn to the emerging phenomena of biology, up to macroscopic levels like diseases observed in living species.

QFVSOOM model relies on a topology of a finite-dimensional vector space on real and complex fields. The unification of the microscopic level to the macroscopic level proposed by QFVSOOM constitutes a significant contribution of this model to quantum mechanics.

Short Biography

Joël Colloc earned his M.D. at the medical faculty of Lyon and a specialty degree of forensic medicine with a degree of clinical toxicology. He received a MSc. degree of IT from the Business School of Lyon (IAE) and a MSc. degree of computer sciences from the engineering school INSA of Lyon. He served as forensic physician at the Edouard Herriot Hospital in the neurological emergency department to cure drug addicted people, medical ethics and developed drug and addiction database. He went on to earn his Ph.D. in computer sciences at the INSA of Lyon.

As Hospital assistant at the laboratory of medical computer science and he taught IT at the medical faculty. He was elected as associate professor in computer sciences at IAE of Lyon and he earned his accreditation to supervise researches in sciences at the Lyon 1 University. He is a Le Havre Normandy University professor in computer sciences since 2003.

His main research topics concern e-health and particularly: fuzzy vectorial spaces (FVS), multi-agent clinical decision support systems (MADSS) and knowledge bases, Case Based Reasoning, ontologies, nervous system modeling and cognitive sciences and AI applications in medicine and human sciences.

His human sciences researches try to conciliate the ethics of using Big Data in epidemiological studies, autonomous systems and robots and keeping ethics use of AI in order to improve clinical decision in medicine while preserving the patient-caregiver relationship, the privacy and the freewill choice of the patients.

Joël Colloc
Université of Le Havre
Le Havre,France