Portrait of Danilo Bzdok

Danilo Bzdok

Core Academic Member
Canada CIFAR AI Chair
Associate Professor, McGill University, Department of Biomedical Engineering


Danilo Bzdok is a computer scientist and medical doctor by training with a unique dual background in systems neuroscience and machine learning algorithms. After training at RWTH Aachen University (Germany), Université de Lausanne (Switzerland) and Harvard Medical School, Bzdok completed two doctoral degrees, one in neuroscience at Forschungszentrum Jülich in Germany, and another in computer science (machine learning statistics) at INRIA–Saclay and the Neurospin brain imaging centre in Paris.

Danilo is currently an associate professor at McGill University’s Faculty of Medicine and a Canada CIFAR AI Chair at Mila – Quebec Artificial Intelligence Institute. His interdisciplinary research centres around narrowing knowledge gaps in the brain basis of human-defining types of thinking in order to uncover key computational design principles underlying human intelligence.

Current Students

Collaborating researcher - Universitat Politècnica
Postdoctorate - McGill University
PhD - McGill University
Postdoctorate - Université de Montréal
Master's Research - McGill University
Master's Research - McGill University
PhD - McGill University
PhD - McGill University
PhD - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University


Data science opportunities of large language models for neuroscience and biomedicine
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Aberrant functional brain network organization is associated with relapse during 1‐year follow‐up in alcohol‐dependent patients
Justin Böhmer
Pablo Reinhardt
Maria Garbusow
Michael Marxen
Michael N. Smolka
Ulrich S. Zimmermann
Andreas Heinz
Eva Friedel
Johann D. Kruschwitz
Henrik Walter
Bayesian modeling disentangles language versus executive control disruption in stroke
Gesa Hartwigsen
Jae‐Sung Lim
Hee-Joon Bae
Kyung‐Ho Yu
Hugo J. Kuijf
Nick A. Weaver
J. Matthijs Biesbroek
Jakub Kopal
Multivariate analytical approaches for investigating brain-behavior relationships
E. Leighton Durham
Karam Ghanem
Andrew J. Stier
Carlos Cardenas-Iniguez
Gabrielle E. Reimann
Hee Jung Jeong
Randolph M. Dupont
Xiaoyu Dong
Tyler M. Moore
Marc G. Berman
Benjamin B. Lahey
Antonia N. Kaczkurkin
The default network dominates neural responses to evolving movie stories
Enning Yang
Filip Milisav
Jakub Kopal
Avram J. Holmes
Georgios D. Mitsis
Bratislav Mišić
Emily S. Finn
Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions
Veronika Pak
Quadri Adewale
Mahsa Dadar
Yashar Zeighami
Yasser Iturria-Medina
For over a century, brain research narrative has mainly centered on neuron cells. Accordingly, most neurodegenerative studies focus on neuro… (see more)nal dysfunction and their selective vulnerability, while we lack comprehensive analyses of other major cell types’ contribution. By unifying spatial gene expression, structural MRI, and cell deconvolution, here we describe how the human brain distribution of canonical cell types extensively predicts tissue damage in thirteen neurodegenerative conditions, including early-and late-onset Alzheimer’s disease, Parkinson’s disease, dementia with Lewy bodies, amyotrophic lateral sclerosis, mutations in presenilin-1, and three clinical variants of frontotemporal lobar degeneration (behavioural variant, semantic and non-fluent primary progressive aphasia) along with associated 3-repeat and 4-repeat tauopathies and TDP43 proteinopathies types A and C. We reconstructed comprehensive whole-brain reference maps of cellular abundance for six major cell types and identified characteristic axes of spatial overlapping with atrophy. Our results support the strong mediating role of non-neuronal cells, primarily microglia and astrocytes, in spatial vulnerability to tissue loss in neurodegeneration, with distinct and shared across-disorders pathomechanisms. These observations provide critical insights into the multicellular pathophysiology underlying spatiotemporal advance in neurodegeneration. Notably, they also emphasize the need to exceed the current neuro-centric view of brain diseases, supporting the imperative for cell-specific therapeutic targets in neurodegeneration.
A hierarchical Bayesian brain parcellation framework for fusion of functional imaging datasets
Da Zhi
Ladan Shahshahani
Caroline Nettekoven
Ana Lúısa Pinho
Jörn Diedrichsen
156. Modeling Eye Gaze to Videos Using Dynamic Trajectory Variability Analysis
Qianying Wu
Na Yeon Kim
Jasmin Turner
Umit Keles
Lynn Paul
Ralph Adolphs
Using rare genetic mutations to revisit structural brain asymmetry
Jakub Kopal
Kuldeep Kumar
Kimia Shafighi
Karin Saltoun
Claudia Modenato
Clara A. Moreau
Guillaume Huguet
Martineau Jean-Louis
Charles-Olivier Martin
C.O. Martin
Zohra Saci
Nadine Younis
Elise Douard
Khadije Jizi
Alexis Beauchamp-Chatel
Leila Kushan
Ana I. Silva
Marianne B.M. van den Bree
David E.J. Linden
M. J. Owen … (see 11 more)
Jeremy Hall
Sarah Lippé
Bogdan Draganski
Ida E. Sønderby
Ole A. Andreassen
David C. Glahn
Paul M. Thompson
Carrie E. Bearden
Robert Zatorre
Sébastien Jacquemont
Genesis, modelling and methodological remedies to autism heterogeneity
Juliette Rabot
Eya‐mist Rødgaard
Ridha Joober
Boris C Bernhardt
Sébastien Jacquemont
Laurent Mottron
Home alone: A population neuroscience investigation of brain morphology substrates
M. Noonan
Chris Zajner
Investigating the neural correlates of affective mentalizing and their association with general intelligence in patients with schizophrenia
Wladimir Tantchik
M. J. Green
Yann Quidé
Susanne Erk
Sebastian Mohnke
Carolin Wackerhagen
Nina Romanczuk-seiferth
Heike Tost
Kristina Schwarz
Carolin Moessnang
Andreas Meyer-Lindenberg
Andreas Heinz
Henrik Walter