Portrait of Danilo Bzdok

Danilo Bzdok

Core Academic Member
bzdokdan@mila.quebec
Canada CIFAR AI Chair
Associate Professor, McGill University, Department of Biomedical Engineering
Research Topics
Computational Biology
Deep Learning
Large Language Models (LLM)
Natural Language Processing

Biography

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

Shambhavi Aggarwal
Master's Research - McGill University
Github
Google Scholar
Badr Ait Hammou
Postdoctorate - McGill University
Gregory Bell
PhD - McGill University
Anwesha Bhattacharya
PhD - McGill University
Liam Hodgson
PhD - McGill University
Ryan McPhedrain McPhedrain
Postdoctorate - McGill University
ryan.mcphedrain@mail.mcgill.ca
David Payette
Master's Research - McGill University
Github
Sepehr Radmannia
Independent visiting researcher - McGill University
sradmannia@gmail.com
Github
Karin Saltoun
PhD - McGill University
Chloé Savignac
PhD - McGill University
Github
Google Scholar
Jack Stanley
PhD - McGill University
Website
Github
Praneet Suresh
PhD - McGill University
Zilong Wang
Master's Research - McGill University
Github
Google Scholar
Le Zhou
PhD - McGill University

Publications

Estimating Unknown Population Sizes Using the Hypergeometric Distribution
Liam Hodgson
Danilo Bzdok
The multivariate hypergeometric distribution describes sampling without replacement from a discrete population of elements divided into mult… (see more)iple categories. Addressing a gap in the literature, we tackle the challenge of estimating discrete distributions when both the total population size and the category sizes are unknown. Here, we propose a novel solution using the hypergeometric likelihood to solve this estimation problem, even in the presence of severe under-sampling. Our approach accounts for a data generating process where the ground-truth is a mixture of distributions conditional on a continuous latent variable, as seen in collaborative filtering, using the variational autoencoder framework. Empirical data simulation demonstrates that our method outperforms other likelihood functions used to model count data, both in terms of accuracy of population size estimate and learning an informative latent space. We showcase our method’s versatility through applications in NLP, by inferring and estimating the complexity of latent vocabularies in reading passage excerpts, and in biology, by accurately recovering the true number of gene transcripts from sparse single-cell genomics data.
2024-07-08
Proceedings of the 41st International Conference on Machine Learning (published)
proceedings.mlr.press
Supervised latent factor modeling isolates cell-type-specific transcriptomic modules that underlie Alzheimer’s disease progression
Liam Hodgson
Yue Li
Yasser Iturria-Medina
Jo Anne Stratton
Guy Wolf
Smita Krishnaswamy
David A. Bennett
Danilo Bzdok
2024-05-17
Communications Biology (published)
doi.org
Data science opportunities of large language models for neuroscience and biomedicine
Danilo Bzdok
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Siva Reddy
2024-02-01
Neuron (published)
doi.org
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
Danilo Bzdok
Eva Friedel
Johann D. Kruschwitz
Henrik Walter
2023-10-02
Addiction Biology (published)
doi.org
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
Danilo Bzdok
2023-08-07
bioRxiv (preprint)
doi.org
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
Danilo Bzdok
Antonia N. Kaczkurkin
2023-07-31
Frontiers in Neuroscience (published)
doi.org
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
Danilo Bzdok
2023-07-14
Nature Communications (published)
doi.org
Distinctive whole-brain cell types predict tissue damage patterns in thirteen neurodegenerative conditions
Veronika Pak
Quadri Adewale
Danilo Bzdok
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.
2023-06-09
bioRxiv (preprint)
doi.org
A hierarchical Bayesian brain parcellation framework for fusion of functional imaging datasets
Da Zhi
Ladan Shahshahani
Caroline Nettekoven
Ana Lúısa Pinho
Danilo Bzdok
Jörn Diedrichsen
2023-05-24
bioRxiv (preprint)
doi.org
156. Modeling Eye Gaze to Videos Using Dynamic Trajectory Variability Analysis
Qianying Wu
Na Yeon Kim
Jasmin Turner
Umit Keles
Lynn Paul
Danilo Bzdok
Ralph Adolphs
2023-05-01
Biological Psychiatry (published)
doi.org
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
Danilo Bzdok
2023-04-18
bioRxiv (preprint)
doi.org
Genesis, modelling and methodological remedies to autism heterogeneity
Juliette Rabot
Eya‐mist Rødgaard
Ridha Joober
Guillaume Dumas
Danilo Bzdok
Boris C Bernhardt
Sébastien Jacquemont
Laurent Mottron
2023-04-01
Neuroscience and Biobehavioral Reviews (published)
doi.org