Danilo Bzdok
Associate Professor
Department of Biomedical Engineering
Canada CIFAR Artificial Intelligence Chair
Mila - Quebec AI Institute
Short Bio:
Danilo Bzdok has earned three different doctoral degrees, with a background in systems neuroscience and machine learning algorithms. After training at RWTH Aachen University (Germany), Universit茅 de Lausanne (Switzerland), and Harvard University (USA), he completed one Ph.D. in cognitive neuroscience (Research Center Juelich, Germany) and one Ph.D. in computer science in machine learning statistics at INRIA Saclay and Neurospin (France). Danilo currently serves as Associate Professor at 麻豆色情片's Faculty of Medicine and as Canada CIFAR AI Chair at Mila - Quebec Artificial Intelligence Institute, Montreal, Canada, including cross-appointments at the McConnell Brain Imaging Center, Montreal Neurological Institute, Ludmer Centre for Neuroinformatics and Mental Health, and the School of Computer Science at 麻豆色情片. His interdisciplinary research activity centers on narrowing knowledge gaps in the brain basis of human-defining types of thinking, with a special focus on the higher association cortex in health and disease.
Research Summary:
Danilo Bzdok鈥檚 research team is focused on data-guided analysis techniques for large datasets from a systems neuroscience perspective. We believe that a strong interdisciplinary approach, with an equal footing in research object and research method, is a prerequisite for forward progress in quantitative neuroscience and personalized medicine. We collaborate with institutions across the globe, identifying pressing questions in biology and health, reframing them as machine learning problems, and translating new insight into biomedicine.听We have been recognized as a world鈥檚 top 1% most cited lab (Clarivate), with previous publications in NeurIPS and ICML as well as Cell, Nature, and PNAS.
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Selected Publications:
Stanley J, Rabot E, Reddy S, Belilovsky E, Mottron L,听Bzdok D.听Large language models decompose the clinical intuition behind diagnosing autism, Cell, 2025.
听Bzdok D, 鈥�, Reddy S.听Data science opportunities for large language models in neuroscience and biomedicine, Neuron, 2024.
听Kopal J, Uddin L,听Bzdok D.听The end game: Respecting major sources of population diversity, Nature Methods, 2023.
听Vasey B, 鈥�,听DECIDE-AI expert group.听Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI, Nature Medicine, 2022.
听Hartwigsen G, Bengio Y,听Bzdok D.听How does hemispheric specialization contribute to human-defining cognition?听Neuron, Cell Press, 2021.
听Bzdok D, Ioannidis JPA.听Exploration, inference and prediction in neuroscience and biomedicine.听Trends in Neurosciences, Cell Press, 42:251-262, 2019.
听Bzdok D, Nichols TE, Smith SM.听Towards Algorithmic Analytics for Large-scale Datasets.听Nature Machine Intelligence, 1:296-306, 2019.
听Bzdok D, Altman N, Krzywinski M.听Statistics versus machine learning.听Nature Methods, 15:233-234, 2018.
听Bzdok D, Eickenberg M, Grisel O, Thirion B, Varoquaux G.听Semi-supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data.听Advances in Neural Information Processing Systems (NeurIPS), 2015.