Bzdok Lab

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 medical imaging and health, reframing them as machine learning problems, and translating new insight into biomedicine.

Bzdok Lab

Meet The Team

Danilo Bzdok

Danilo Bzdok

Principal Investigator

McGill University

Mila Institute

Danilo Bzdok is a medical doctor and computer scientist with a dual background in systems neuroscience and machine learning algorithms. After medical training at RWTH Aachen University (Germany), Université de Lausanne (Switzerland), and Harvard Medical School (USA), he completed one Ph.D. in brain-imaging neuroscience (Research Center Juelich, Germany, 2012) and one Ph.D. in computer science in machine learning statistics at INRIA Saclay and Neurospin (France, 2016). 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, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, and the School of Computer Science at McGill University. In his free time, he enjoys French and Italian culture, language and languages, playing chess or Go, and consuming excessive amounts of music.


Vaibhav Sharma

Vaibhav Sharma

Research Associate

McGill University

Vaibhav completed his bachelor’s in computer science & engineering from NIT, Allahabad, and Master’s in computer science from the University of Utah, Salt Lake City. He has worked in multinational corporations like Microsoft, Cisco, Intel, Nuance, and different startups in myriads of technical roles. Vaibhav is currently working as a Research Associate, where he uses his software expertise to push boundaries in interdisciplinary research using large-scale medical and imaging databases. Vaibhav is always eager to learn new skills and loves sharing knowledge to empower the team. He has had many hobbies during different phases of his life, frankly too many to mention. Once upon a time, he also worked in Bollywood.


Jakub Kopal

Jakub Kopal

Postdoctoral Fellow

McGill University

University of Montreal

Jakub Kopal completed his Ph.D. in neuroscience under joint supervision from the University of Chemistry and Technology in Prague (Czechia) and Université Toulouse III – Paul Sabatier (France) in 2021. Currently, he is working as a postdoctoral fellow at the intersection of neuroscience and genetics in the group of Danilo Bzdok at McGill University and Sébastien Jacquemont at the University of Montreal. His research interests include neuroscience and data analysis, with a particular focus on the role of connectivity in brain functioning. Otherwise, he likes pickles and random facts.


Liam Hodgson

Liam Hodgson

Doctoral Student

McGill University

Prior to joining the Bzdok Lab at McGill, Liam completed his bachelor’s degree in Engineering Physics at UBC and subsequently worked on the R&D team at an additive manufacturing startup. As a doctoral student in the Computer Science department, he is investigating the function and disfunction of the human brain through the lens of single-cell omics, as well as developing computational methods to better analyze and interpret this high-dimensional biological data.


Jack Stanley

Jack Stanley

Doctoral Student

McGill University

Jack is a PhD student in the Quantitative Life Sciences program at McGill. Prior to joining the lab, Jack completed an Honours BSc in Statistics and Biochemistry at the University of Toronto, where he was a Schulich Leader and National Scholar. His current research is focused on untangling the complexity of human disease and biology using increasingly powerful deep learning approaches. An avid distance runner, Jack is also captain of McGill’s varsity cross country team, and a member of the varsity track team.


Chloé Savignac

Chloé Savignac

Master’s Student

CIHR & FRQNT Fellow

McGill University

Chloé Savignac is an MSc student in Neuroscience at McGill University interested in human-defining cognition, especially language and prosocial behaviours. She joined the lab in January 2021 after graduating First Class Honours from a B.A. & Sc. in Cognitive Science at McGill University. Her current research efforts are focused on applying tools from Big Data analytics to answer long-standing neuroscience questions in population datasets. As part of her master’s degree, Chloé is investigating the co-variation between the hippocampus and default network in populations of healthy individuals at risk of Alzheimer’s disease. Outside the lab, Chloé enjoys learning how to cook new vegan recipes and salsa dancing.


Enning Yang

Enning Yang

Master’s Student

McGill University

Enning is interested in how neuroscience can boost AI techniques and how AI could help solve neuroscience problems. Currently, he is working on representation learning problems of neuroimaging. Fun Fact: One of his hobbies is cooking and he wishes to have a fine dining restaurant in the future.


Karin Saltoun

Karin Saltoun

Master’s Student

McGill University

Karin Saltoun is a M.Sc student in Neuroscience at McGill University. She studied biophysics at York University (Toronto) where she developed a love for using math and physics to understand biological problems on a more fundamental level. During her undergraduate career, first through work in an experimental lab focusing on precision measurements in atomic physics, before moving to a computational neuroscience lab developing algorithms for distinguishing sleep states from brain behaviour. She is currently working in Dr. Bzdok’s lab to understand brain asymmetry at a population level using a variety of machine learning techniques. When she’s not glued to her computer, she enjoys baking desserts or reading fiction.


Kimia Shafighi

Kimia Shafighi

Master’s Student

McGill University

Kimia is starting her Master’s in the Integrated Program of Neuroscience at McGill University after receiving her bachelor’s in biomedical engineering. She dedicated her undergraduate studies to create the McGill Biodesign team and worked on transformational applications in biotechnology. Now, she is using machine learning techniques to investigate a variety of neuroscience questions at the population scales and discover statistical patterns in large datasets.


Karam Ghanem

Karam Ghanem

Master’s Student

McGill University

Karam Ghanem is starting his Masters in Biomedical Engineering at McGill University. He finished his Bachelor’s degree in Engineering Physics at McMaster University where he immersed himself in the application of physics in a number of engineering and scientific fields. Karam worked as a Firmware Engineer on the R&D team at a telecommunications company where he developed his engineering skillset. He developed a curiosity for the role of the human brain in relation to the physical world and human experiences and wants to answer his own questions with his research. He is currently working in Dr. Bzdok’s lab to understand structural plasticity in the amygdala at a subregion level in relationship to the plasticity in the rest of the brain due to learning at a population level using a variety of machine learning techniques. Karam has a love for music; he plays the oud and dabbles with other instruments.


Justin Marotta

Justin Marotta

Master’s Student

McGill University

Justin is a student in the Biological & Biomedical Engineering Master’s program at McGill. Prior to joining the lab, he completed his undergraduate degree in Electrical Engineering at Queen’s University and worked as a sales engineer for Cisco Systems focused on cybersecurity solutions. Driven by a passion for learning and problem solving, Justin is excited to work in a multidisciplinary team investigating problems in neuroscience through machine learning techniques. In his free time he enjoys music, reading, and getting outside to ski and hike.


Zilong Wang

Zilong Wang

Master’s Student

McGill University

Zilong is starting his MSc in Neuroscience at McGill University, after graduating from Honors Cognitive Science also at McGill. He is interested in understanding human higher cognitive functions by applying various machine learning methods on large population data. Currently he is investigating the relationship between different cerebellum subregions and cortical areas to learn more about the novel functions recently discovered in cerebellum. In his free time, Zilong enjoys meeting people and welcomes any outdoor activities.


Nicole Osayande

Nicole Osayande

Master’s Student

McGill University

Nicole is a Master’s student in the Biological & Biomedical Engineering program, and she was selected for the inaugural cohort of McCall MacBain Scholars at McGill. She graduated from Queen’s University in spring of 2021 with a bachelor’s degree in Computer Science, specializing in Biomedical Computing. Prior to joining the lab, Nicole worked at IBM as a software developer for the Watson Orchestrate AI team, where she gained hands-on experience with machine learning algorithms and automation tools. Nicole has a strong connection to EDI initiatives as she founded the Queen’s Student Diversity Project at her alma mater and collaborated with the undergraduate admissions and recruitments office to encourage students of diverse backgrounds to pursue their post-secondary studies at Queen’s. She now hopes to bridge her interest in machine learning with her passion for EDI initiatives to introduce the Neuroscience community to diversity-aware population modeling of large-scale datasets via Bayesian hierarchical regression. In her free time, she likes dancing, boxing, content creation, and watching Korean dramas!


Future Lab Members


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Le Zhou

Incoming PhD Student

Former Lab Members


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Chris Zajner

Research Assistant 2020-2021

Pursuing medical studies at Western University.

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Nadejda Zaharieva

Lab Manager & RA 2021

Research at École de technologie supérieure.

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Nahiyan Malik

Master's Student 2019-2021

Meta Platforms, Inc.

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Julius Kernbach

Doctoral student 2017-2019

Neurosurgeon at RWTH Aachen Medical School

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Anthony Ma

Bachelor Student 2018-2022

Pursuing masters at Harvard University

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Hannah Kiesow

Doctoral student 2018-2022

Senior Psychologist at Zortify

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Hasnain Mamdani

Master's Student 2019-2021

Data Scientist at Hamilton Health Sciences

Publications

A complete list of our publications can be found on ResearchGate.

Selected Publications

Bzdok D, Altman N, Krzywinski M. Statistics versus machine learning. Nature Methods, 2018, 15:233-234.
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, Engemann D, Thirion B. Inference and prediction diverge in biomedicine. Patterns, Cell Press, 2020.
Hartwigsen G, Bengio Y, Bzdok D. How does hemispheric specialization contribute to human-defining cognition? Neuron, Cell Press, 2021.
Smallwood J, Bernhardt B, Leech R, Bzdok D, Jefferies E, Margulies D. The role the default mode network in cognition: a topographic perspective. Nature Reviews Neuroscience, 2021.
Kernbach J, Yeo BTT, Smallwood J, Margulies D, Thiebaut de Schotten M, Walter H, Sabuncu M, Holmes A, Gramfort A, Varoquaux G, Thirion B, Bzdok D. Subspecialization within Default Mode Nodes Characterized in 10,000 UK Biobank Participants. Proceedings of the National Academy of Sciences of the USA, 115:12295-12300, 2018.
Kiesow H, Dunbar RIM, Kable JW, Kalenscher T, Vogeley K, Schilbach L, Marquand AF, Wiecki TV, Bzdok D. 10,000 Social Brains: Sex Differentiation in Human Brain Anatomy. Science Advances, AAAS journal, 6:aaz1170, 2020.
Schulz MA, Yeo BTT, Vogelstein JT, Mourao-Miranada J, Kather JN, Kording K, Richards B, Bzdok D. Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets. Nature Communications, 2020.
Spreng RN, Dimas E, Mwilambwe-Tshilobo L, Dagher A, Koellinger P, Nave G, Ong A, Kernbach JM, Wiecki TV, Ge T, Li Y, Holmes A, Yeo BTT, Dunbar RIM, Bzdok D. The Default Network of the Human Brain Is Associated With Perceived Social Isolation. Nature Communications, 2020.
Bzdok D, Michael Eickenberg, Gaël Varoquaux, Bertrand Thirion. Hierarchical Region-Network Sparsity for High-Dimensional Inference in Brain Imaging. Information Processing in Medical Imaging (IPMI), 2017, pp. 323-335.
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.

Teaching

Related teaching on machine learning/data science:

Course outline from 2020 for BMDE 520
Course outline from 2021 for BMDE 520/COMP 598
Course outline for 2022 for BMDE 520/COMP 598

Contact

Dr. Danilo Bzdok is currently looking for post-docs, PhD students, and software engineers to build the labs at McGill University and Mila Artificial Intelligence Institute in Montreal, Canada. Drop him an if you are interested.

  • Department of Biomedical Engineering, Faculty of Medicine, McGill University, 3775 Rue University, Montréal, QC H3A 2B4
  • 09:00 to 17:00 Monday to Friday
  • Publications

McGill University Mila Institute