Portrait of Tal Arbel

Tal Arbel

Core Academic Member
Canada CIFAR AI Chair
Full Professor, McGill University, Department of Electrical and Computer Engineering
Research Topics
Causality
Computer Vision
Deep Learning
Generative Models
Medical Machine Learning
Probabilistic Models
Representation Learning

Biography

Tal Arbel is a professor in the Department of Electrical and Computer Engineering at McGill University, where she is the director of the Probabilistic Vision Group and Medical Imaging Lab in the Centre for Intelligent Machines.

She is also a Canada CIFAR AI Chair, an associate academic member of Mila – Quebec Artificial Intelligence Institute and an associate member of the Goodman Cancer Research Centre.

Arbel’s research focuses on the development of probabilistic deep learning methods in computer vision and medical image analysis for a wide range of real-world applications, with a focus on neurological diseases.

She is a recipient of the 2019 McGill Engineering Christophe Pierre Research Award and regularly serves on organizing committees for major international conferences in computer vision and medical image analysis, including for the Medical Image Computing and Computer-Assisted Intervention Society/MICCAI, the Medical Imaging with Deep Learning/MIDL, the International Conference on Computer Vision/ICCV or the Computer Vision and Pattern Recognition Conference/CVPR). She co-founded the arXiv overlay journal, Machine Learning for Biomedical Imaging (MELBA) and is currently its editor-in-chief.

Current Students

Postdoctorate - McGill University
PhD - McGill University
Master's Research - McGill University
Master's Research - McGill University
PhD - McGill University
Master's Research - McGill University
Master's Research - McGill University
PhD - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University
Undergraduate - McGill University
Undergraduate - McGill University

Publications

Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis
M. Jorge Cardoso
Su-Lin Lee
Veronika Cheplygina
Simone Balocco
Diana Mateus
Guillaume Zahnd
Lena Maier-Hein
Stefanie Demirci
Éric Granger
Luc Duong
M. Carbonneau
Shadi N. Albarqouni
G. Carneiro
Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment
M. Cardoso
Fei Gao
BERNHARD KAINZ
T. Walsum
Kuangyu Shi
Kanwal K. Bhatia
R. Peter
Tom Kamiel Magda Vercauteren
Mauricio Reyes
Adrian Dalca
Roland Wiest
W. Niessen
B. Emmer
Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment
M. Jorge Cardoso
Fei Gao
BERNHARD KAINZ
T. Walsum
Kuangyu Shi
Kanwal K. Bhatia
R. Peter
Tom Kamiel Magda Vercauteren
Mauricio Reyes
Adrian Dalca
Roland Wiest
Wiro Niessen
B. Emmer
Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging
Henning Müller
B. Kelm
Weidong (Tom) Cai
M. Jorge Cardoso
Georg Langs
Bjoern Menze
Dimitris N. Metaxas
Albert A. Montillo
William Wells
Shaoting Zhang
Albert C.S. Chung
M. Jenkinson
Annemie Ribbens
Clinical Image-Based Procedures. Translational Research in Medical Imaging
Ian J. Gerard
Marta Kersten-Oertel
Simon Drouin
Jeffery Alan Hall
Kevin Petrecca
Dante De Nigris
D. Collins
Bayesian and grAphical Models for Biomedical Imaging
M. Cardoso
Ivor J. A. Simpson
Annemie Ribbens
Bayesian and grAphical Models for Biomedical Imaging
M. Jorge Cardoso
Ivor J. A. Simpson
Annemie Ribbens