Danilo Bzdok
Associate Professor
Department of Biomedical Engineering
Canada CIFAR Artificial Intelligence Chair
Mila - Quebec AI Institute
Our lab has been recognized as a world’s top 1% most cited lab (Clarivate), with previous publications in NeurIPS and ICML as well as Cell, Nature, and PNAS.
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), Université 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 McGill'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 McGill University. 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’s 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.
Keywords:
Neuroimaging
Complex Networks
Machine Learning
Cognitive Process
Brain Functional Modeling
Big Data
Bayesian Hierarchical Modeling
Suresh P, Stanley J, Joseph S, Scimeca L, Bzdok D. From noise to narrative: Tracing the origins of hallucinations in transformers, Neural Information Processing Systems (NeurIPS), 2025.
Stanley J, Rabot E, Reddy S, Belilovsky E, Mottron L, Bzdok D. Large language models decompose the clinical intuition behind diagnosing autism, Cell, 2025.
Bzdok D, …, Reddy S. Data science opportunities for large language models in neuroscience and biomedicine, Neuron, 2024.
Kopal J, Uddin L, Bzdok D. The end game: Respecting major sources of population diversity, Nature Methods, 2023.
Vasey B, …, DECIDE-AI expert group. Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI, Nature Medicine, 2022.
Hartwigsen G, Bengio Y, Bzdok D. How does hemispheric specialization contribute to human-defining cognition? Neuron, Cell Press, 2021.
Bzdok D, Ioannidis JPA. Exploration, inference and prediction in neuroscience and biomedicine. Trends in Neurosciences, Cell Press, 42:251-262, 2019.
Bzdok D, Nichols TE, Smith SM. Towards Algorithmic Analytics for Large-scale Datasets. Nature Machine Intelligence, 1:296-306, 2019.
Bzdok D, Altman N, Krzywinski M. Statistics versus machine learning. Nature Methods, 15:233-234, 2018.
Bzdok D, Eickenberg M, Grisel O, Thirion B, Varoquaux G. Semi-supervised Factored Logistic Regression for High-Dimensional Neuroimaging Data. Advances in Neural Information Processing Systems (NeurIPS), 2015.