NEASQC webinar: Managing uncertainty in AI with Quantum Computing

Date: 2 October 2024
Time: 11:00-12:00 CEST

NEASQC is organising a series of interactive webinars to share our findings with the quantum computing community. Each month NEASQC experts present an Open Source library available in the NEASQC GitHub or a technique they investigated, and answer your questions.

In October, we will present some outcomes of the NEASQC use case on Quantum rule-based systems (QRBS) for breast cancer detection.

Abstract: With the raise of Big Data and AI systems that have taken over most industries in the last years, there has come afloat a problem which can be difficult to address: uncertainty. From incomplete data to disagreement between experts, uncertainty is a key aspect of information when solving any reasoning problem. Here, we present a new approach: to use the intrinsic probabilistic nature of Quantum Computing to represent and manage uncertain information, developing several models that allow for the implementation of AI systems in quantum machines. With this proposal, users can model their systems classically, defining the different facts and rules that compose their inference process, and translate it into a quantum circuit that operates with uncertainty seamlessly. In this webinar, we present the theoretical base of the work, reviewing the elements of classical AI systems, and how we can take these structures into the world of Quantum Computing.

Speakers: Emeritus Professor Vicente Moret-Bonillo & PhD student Samuel Magaz-Romero, Universidade da Coruña

Vicente Moret-Bonillo graduated in Chemistry (B.Sc. Fundamental Chemistry, Major in Physical Chemistry, 1984) and received his Ph.D. (Applied Physics, 1988) in University of Santiago de Compostela, Spain. He was a Post-Doctoral Research Fellow Biomedical Engineering Department (1988-1990) in Medical College of Georgia, USA, and received the Award of Merit for Significant Contribution in the Field of Clinical Engineering (Quest Publishing Eds, USA, 1990). Currently he is a Emeritus Professor Computer Science in Universidade da Coruña, Spain.

Samuel Magaz-Romero received his B.Sc. in Computer Science (2020) and his M.Sc. in Software Engineering (2022) in Universidade da Coruña, Spain. He is currently pursuing his Ph.D. in Computer Science under the direction of Prof. Vicente Moret-Bonillo and Prof. Eduardo Mosqueira-Rey. His thesis revolves around researching Quantum Computing techniques to represent uncertainty in Artificial Intelligence systems, his two main areas of interest.

Related publications

• D6.14: Final QRBS software and IDC application (report)
  The corresponding software is in the NEASQC GitHub, check https://neasqc.github.io/qrbs/index.html
• And all the publications listed on the use case webpage https://www.neasqc.eu/use-case/algorithms-for-the-diagnosis-of-invasive-ductal-carcinoma/