Karim Jerbi is a Professor in the Department of Psychology at the University of Montreal, where he holds a Canada Research Chair (Tier 2) in Computational Neuroscience and Cognitive Neuroimaging. He is the Director of UNIQUE, the Quebec-wide Neuro-AI Research Center, and an Associate Professor at Mila, the Quebec AI research institute. Dr. Jerbi earned a PhD in Cognitive Neuroscience and Brain Imaging from Pierre and Marie Curie University in Paris and holds a degree in Biomedical Engineering from the University of Karlsruhe, Germany. His research sits at the intersection of cognitive, computational, and clinical neuroscience. The work conducted in his laboratory focuses on elucidating the role of neural oscillations and large-scale brain communication in cognition—including decision-making, attention, consciousness, and creativity—and on investigating brain network alterations in psychiatric and neurological disorders. His multidisciplinary research program combines advanced brain-imaging methods, such as magnetoencephalography (MEG) and scalp and intracranial electroencephalography (EEG), with state-of-the-art signal processing, computational modeling, and data analytics, including machine learning. Dr. Jerbi also has a strong interest in the convergence of neuroscience, artificial intelligence, and art, as well as in promoting justice within and beyond the scientific community. In his role as Director of the UNIQUE Neuro-AI Research Center at Université de Montréal, Dr. Jerbi contributes expertise on the intersections of cognitive, computational, and clinical neuroscience, and on how knowledge frameworks from diverse cultural contexts shape our understanding of intelligent action.

Guillaume Dumas is an Associate Professor of Computational Psychiatry at the Université de Montréal and Principal Investigator of the Precision Psychiatry and Social Physiology Laboratory at the CHU Sainte-Justine Research Center. He holds the IVADO Professorship in “AI in Mental Health” and the FRQS J1 in “AI and Digital Health.” Previously, he was a permanent researcher at the Institut Pasteur (Paris) and a postdoctoral fellow at the Center for Complex Systems and Brain Sciences (FAU, USA). He holds an engineering degree from École Centrale Paris, two MSc degrees in theoretical physics and cognitive science, and a PhD in cognitive neuroscience from Sorbonne University. His research aims at cross-fertilizing AI/ML, cognitive neuroscience, and digital medicine through an interdisciplinary program with two main axes: AI/ML for Mental Health, creating new algorithms to investigate the development of human cognitive architecture and to deliver personalized medicine in neuropsychiatry using data from genomes to smartphones; and Social Neuroscience for AI/ML, translating basic brain research and dynamical systems formalism into neurocomputational and machine learning hybrid models (NeuroML) and machines with social learning ability (Social NeuroAI & HMI). He co-developed the first graduate course in computational medicine at Université de Montréal and participates in numerous projects at the interface between science and society, from raising awareness about altered states of consciousness (co-founder of Alius Research, 2007) and open science (co-founder of HackYourResearch, 2012) to advising governments about AI (expert for the two French AI national strategic plans) and fighting for cognitive freedom (twice invited expert at the United Nations Human Rights Council). He brings expertise in AI for Mental Health and Social Neuroscience for AI to advance interdisciplinary approaches in computational psychiatry.

Dr. ʻŌiwi Parker Jones leads the Neural Processing Lab (PNPL) in the Department of Engineering Science at the University of Oxford. His primary research interest is in the development of effective non-invasive Brain Computer Interfaces (BCIs) for people who cannot speak. This includes basic research on speech and language in the brain, and the development of powerful new deep learning methods for neural data. When he has spare compute cycles, Parker Jones also works on Automatic Speech Recognition for the Hawaiian language, which he grew up speaking as part of the Pūnana Leo O Hilo, Kula Kaiapuni O Keaukaha, and Nāwahīokalaniʻōpuʻu. He completed a Doctor of Philosophy at the University of Oxford focused on Natural Language Processing (NLP) for low-resource languages. He further trained as a postdoc in Imaging Neuroscience at UCL and Oxford, and in Applied Artificial Intelligence in Oxford. Previously, he was a lecturer in Medicine at St Peter’s College, Oxford, and is currently Hugh Price Fellow in Computer Science at Jesus College, Oxford, and one of seven Principal Investigators at the Oxford Robotics Institute.

Dr. Melanie Cheung (Ngāti Rangitihi, Te Arawa) is a neurobiologist with experience across academia, the health sector, and Indigenous communities in Aotearoa, Canada, and the USA. Her research focuses on understanding how neuroplasticity can be harnessed to develop neurological treatments and enhance performance. Her work is distinguished by its integration of innovative, multidisciplinary science—including brain training, neurodegenerative disease research, MRI, neuropsychology, and biomarkers—with clinical practice in psychiatry, community-based care, and Māori healing. She also incorporates decolonising methodologies, grounding research ethics and practices in Māori concepts and engaging intensively with Māori communities. In recognition of her contributions, Dr Cheung has received the Women of the Year Award in Health and Science and the Huntington’s Disease Society of America Distinguished Leadership Award for exemplary dedication.

Ceyda Yolgörmez is a Postdocoral Researcher at the Indigenous Futures Research Cluster, working in the Abundant Intelligences Research Program. Her PhD work brought together social theory and interactive technologies, such as large machine learning models or social robots, to consider how our conceptions of the social are changing. Her PhD dissertation proposes a framework for a sociology of machines that reimagines human-machine relations. Her research looks at playful and creative engagements with machines as a site to explore and experiment with human machine socialities, and is interested in methodologies that reveal and trouble the common-sensical way in which we understand such relations.