Prof. Georgios Kontaxakis
Universidad Politécnica de Madrid, Spain

Title: Artificial Intelligence for Brain–Computer Interfaces: From Neural Signals to Intelligent Neurotechnologies

Abstract: The convergence of artificial intelligence (AI) and neurotechnology is redefining how we interface with the brain. Advances in deep learning, adaptive signal processing, and computational neuroscience have enabled Brain–Computer Interfaces (BMIs) to evolve from basic neural decoding systems into intelligent, context-aware technologies capable of learning from users and adapting to changing neural dynamics. This talk will explore the transformative role of AI in BMI research, focusing on recent developments that enhance neural decoding accuracy, user adaptability, and closed-loop control for neurorehabilitation and assistive robotics. Special attention will be given to machine learning strategies—such as reinforcement learning, transfer learning, and hybrid AI–signal processing pipelines—that are accelerating the transition from laboratory prototypes to clinically and functionally relevant systems. The presentation draws on ongoing interdisciplinary research at the Universidad Politécnica de Madrid (UPM), where advances in biomedical engineering, neuroscience, and computational intelligence converge to develop adaptive EEG-based interfaces, motor imagery systems, and wearable neurodevices. Examples from UPM’s neurotechnology and biomedical signal processing laboratories, as well as from our international research labs, will illustrate how AI can improve signal reliability, personalization, and interpretability in practical BCI applications. Beyond technical progress, the talk will address ethical considerations, data management, and the need for explainable and responsible AI in human-centered neurotechnologies. By integrating engineering precision with neurobiological insight, AI-powered BMIs point toward a new generation of intelligent systems capable of restoring, augmenting, and understanding human function—bringing the vision of seamless brain–machine interaction closer to reality.

BIO: Giorgos Kontaxakis, Ph.D., Senior Member of the IEEE, is with the Department of Electronic Engineering at the Universidad Politécnica de Madrid (UPM), Spain, where he leads research at the intersection of biomedical engineering, signal processing, and neurotechnology. He studied Electrical and Computer Engineering at the National Technical University of Athens (Greece) and holds both an M.Sc. and Ph.D. in Biomedical Engineering from Rutgers, The State University of New Jersey (USA).

Dr. Kontaxakis was a postdoctoral fellow at the German Cancer Research Center in Heidelberg, Germany; a visiting researcher at Macquarie University in Sydney, Australia; and a project manager at the Fraunhofer Institute for Computer Graphics in Darmstadt, Germany. He joined UPM in 2000 as a Marie Curie Fellow, later became a Ramón y Cajal Senior Researcher, and obtained tenure in 2008. During his sabbatical leave (2016–2017), he served as a Visiting Professor of Radiology at Harvard Medical School and as a Visiting Researcher at the Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, sponsored by a fellowship from the Real Colegio Complutense at Harvard.

He has published over 200 peer-reviewed journal articles, conference papers, and book chapters spanning domains such as biomedical imaging (particularly positron emission tomography, PET), algorithm development, computational methods for biomedical signals, and neuroengineering applications. Over the course of his career, he has applied Monte Carlo simulations, optimization methods, machine learning tools, and multimodal integration techniques to challenges in medical and neural systems. More recently, his work has expanded into neurotechnology, brain–computer interfaces (BCI), EEG/BCI signal processing, and translational systems that bridge neural measurement with intelligent software. This aligns with his current leadership of UPM’s new Master of Science in Neurotechnology, established in the 2024–2025 academic year.

Beyond research, Dr. Kontaxakis plays an active role in training and mentoring students in interdisciplinary fields that combine neuroscience, engineering, and computation. He is committed to fostering innovation in neural interfaces and to developing intelligent systems capable of interpreting neural signals in real-world contexts. He is also active in international collaborations, peer review, and in promoting open science practices within his disciplines. Since 2001, he has served on numerous occasions as chair, vice-chair, and evaluator in proposal evaluation and project review panels for the European Commission and its agencies, as well as for other national and international agencies.

His vision is to advance systems that seamlessly integrate brain data, computational modeling, and adaptive interfaces, driving innovation in neurorehabilitation, assistive devices, and human–machine integration.