Quantum generative models for healthcare
Abstract: This talk will focus on the young discipline of quantum machine learning (QML), which is focused on the design, development and application of novel methods for data analysis based on quantum computing, Quantum computing is known to outperform classical computers in tasks such as unstructured search (Grover’s algorithm) and factorization (Shor’s algorithm), fundamental to applications such as cryptography. QML explores the potential benefits of quantum representations and mechanisms such as superposition and entanglement for massively parallel processing. Current research is limited by the state of quantum technology, which is in its infancy but developing at an impressive pace. We will explore links with generative AI models, presenting the main types of generative models and their potential adaptations to quantum-based methods.
Biosketch: Prof. Miguel A. González Ballester holds an MEng from Universitat Jaume I, Spain (1996) and a PhD from the University of Oxford, UK (2000). His doctorate, under supervision of Sir Michael Brady and Prof. Andrew Zisserman, focused on the analysis of brain MRI data for multiple sclerosis and schizophrenia. He was awarded the prestigious Toshiba Research Fellowship and moved to Japan to work for two years as a senior researcher at Toshiba Medical Systems, where he developed novel, patented systems for MRI parallel imaging. In late 2001 he obtained a faculty position at INRIA (Sophia Antipolis, France), where he led research projects on medical image analysis and mathematical modelling. In 2004 he joined the University of Bern (Switzerland), as head of the medical image analysis group, and later became head of the surgical technology division at the Faculty of Medicine. There, he supervised a division composed of 4 research groups working on medical image analysis, computer-assisted surgery, and surgical robotics and mechatronics. From 2008 until September 2013 he was in charge of the Research Department of the company Alma IT Systems in Barcelona (Spain), where he led the development of a new generation of computer tools for diagnosis and surgical planning. In October 2013 he was awarded an ICREA Research Professorship, and joined the Department of Information and Communication Technologies at Universitat Pompeu Fabra in Barcelona, where he founded the Barcelona Center for New Medical Technologies (BCN Medtech). He has more than 130 publications in peer-reviewed scientific journals and 300 conference publications, and has supervised to completion 22 PhD theses. He is also co-founder and scientific advisor of the company MiWEndo Solutions S.L., and a Visiting Scientist at the QUANTIC research group of Barcelona Supercomputing Center, where he focuses his research on quantum machine learning.
