Jose Dolz

Associate Professor
ETS Montreal
Laboratory for Image, vision and AI (LIVIA)
Montreal, CA

Email: jose dot dolz at etsmtl dot ca

Short-Bio

I am an Associate Professor in the Department of Software and IT Engineering at the ETS Montreal. Prior to be appointed Professor, I was a post-doctoral fellow at the same institution. I obtained my B.Sc and M.Sc in the Polytechnic University of Valencia, Spain, and his Ph.D. at the University of Lille 2, France, in 2016. I was recipient of a Marie-Curie FP7 Fellowship (2013-2016) to pursue my doctoral studies. My current research focuses on deep learning, medical imaging, optimization and learning strategies with limited supervision. Up to date, I have (co-)authored over 80 fully peer-reviewed papers, many of which published in the top venues in medical imaging (MICCAI/IPMI/MedIA/TMI/NeuroImage), computer vision (CVPR, ICCV) and machine learning (ICML, NeurIPS). Furthermore, I have given 5 tutorials on learning with limited supervision at MICCAI (2019-2022) and ICPR(2022), participated in the organization of three summer schools in Deep Learning for Medical Imaging and recognized several times as Outstanding Reviewer (MICCAI'20, ECCV'20, CVPR'21, CVPR'22, NeurIPS'22, ICCV'23).

News

[03/2024] I am acting as Area Chair at ECCV 2024.
[03/2024] Two papers accepted at CVPR'24.
[11/2023] Two recent papers accepted at MedIA: Do We Really Need Dice? The Hidden Region-Size Biases of Segmentation Losses Paper Anatomically-aware Uncertainty for Semi-supervised Image Segmentation Medical Image Analysis Paper
[07/2023] One paper accepted at ICCV'23.
[06/2023] Two papers accepted at MICCAI'23.
[03/2023] Two papers accepted at CVPR'23.
[02/2023] Two papers accepted at IPMI'23 (both as oral).
[01/2023] I am acting as Area Chair at MICCAI 2023.
[01/2023] One paper accepted at MedIA: Mixed-supervised segmentation: Confidence maximization helps knowledge distillation Paper Code
[10/2022] One paper accepted at MedIA: Constrained unsupervised anomaly segmentation Paper Code
[06/2021] One paper accepted at MICCAI'22: Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation Paper
[03/2022] One paper accepted at CVPR'22: The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration Paper Code
[01/2022] One paper accepted at MedIA: Weakly supervised segmentation with cross-modality equivariant constraints Paper Code
[01/2022] I am acting as Area Chair at MICCAI 2022.
[01/2022] I will be part of the technical committee of MIDL for the next 3 years (2022-2024).
[06/2021] One paper accepted at MICCAI'21: Orthogonal Ensemble Networks for Biomedical Image Segmentation Paper Code
[02/2021] I am acting as Area Chair at MICCAI 2021.

Selected Publications [Google Scholar]

	A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models. Silva-Rodriguez, Sina Hajimiri, Ismail Ben Ayed, Jose Dolz CVPR 2024. [PDF] [CODE]
	LP++: A Surprisingly Strong Linear Probe for Few-Shot CLIP. Yunshi Huang, Fereshteh Shakeri, Jose Dolz, Malik Boudiaf, Houda Bahig, Ismail Ben Ayed CVPR 2024 Code and Arxiv coming soon.
	Do We Really Need Dice? The Hidden Region-Size Biases of Segmentation Losses. Bingyuan Liu, Jose Dolz, Adrian Galdran, Riadh Kobbi, Ismail Ben Ayed MedIA 2024. [PDF][CODE]
	Anatomically-aware Uncertainty for Semi-supervised Image Segmentation. Sukesh V Adiga, Jose Dolz, Hervé Lombaert MedIA 2024. [PDF][CODE]
	Parametric Information Maximization for Generalized Category Discovery. Florent Chiaroni,Jose Dolz, Ziko Imtiaz Masud, Amar Mitiche, Ismail Ben Ayed ICCV 2023. [PDF]
	Trust your neighbours: Penalty-based constraints for model calibration. Balamurali Murugesan, Sukesh Adiga V, Bingyuan Liu, Hervé Lombaert, Ismail Ben Ayed, Jose Dolz MICCAI 2023. [PDF] [CODE]
	Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation. Agostina Larrazabal, Cesar Martinez,Jose Dolz, Enzo Ferrante MICCAI 2023. [PDF]
	A Strong Baseline for Generalized Few-Shot Semantic Segmentation. Sina Hajimiri, Malik Boudiaf, Ismail Ben Ayed, Jose Dolz CVPR 2023. [PDF][CODE]
	Class Adaptive Network Calibration. Bingyuan Liu, Jerome Rony, Adrian Galdran, Jose Dolz, Ismail Ben Ayed CVPR 2023. [PDF] [CODE]
	Harmonizing Flows: Unsupervised MR harmonization based on normalizing flows. Farzad Beizaee, Christian Desrosiers, Gregory A Lodygensky, Jose Dolz IPMI 2023, Oral Presentation. [PDF] [CODE]
	Mixup-Privacy: A simple yet effective approach for privacy-preserving segmentation. Bach Ngoc Kim, Jose Dolz, Pierre-Marc Jodoin, Christian Desrosiers IPMI 2023, Oral Presentation.
	Calibrating Segmentation Networks with Margin-based Label Smoothing. Balamurali Murugesan, Bingyuan Liu, Adrian Galdran, Ismail Ben Ayed, Jose Dolz MedIA 2023. [PDF] [CODE]
	GeoLS: Geodesic Label Smoothing for Image Segmentation. Sukesh V Adiga, Jose Dolz, Herve Lombaert MIDL 2023, Oral Presentation. [PDF]
	Segmentation with mixed supervision: Confidence maximization helps knowledge distillation. Bingyuan Liu, Christian Desrosiers, Ismail Ben Ayed, Jose Dolz MedIA 2023. [PDF] [CODE]
	Constrained unsupervised anomaly segmentation. Julio Silva-Rodriguez, Valery Naranjo, Jose Dolz MedIA 2022. [PDF] [CODE]
	Source-Free Domain Adaptation for Image Segmentation Mathilde Bateson, Hoel Kervadec, Jose Dolz, Hervé Lombaert, Ismail Ben Ayed MedIA 2022. [PDF] [CODE]
	Leveraging Labeling Representations in Uncertainty-based Semi-supervised Segmentation Sukesh V Adiga, Jose Dolz, Hervé Lombaert MICCAI 2022. [PDF]
	The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration Bingyuan Liu, Ismail Ben Ayed, Adrian Galdran, Jose Dolz CVPR 2022. [PDF] [CODE]
	Weakly supervised segmentation with cross-modality equivariant constraints Gaurav Patel, Jose Dolz MedIA 2022. [PDF] [CODE]
	Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? Malik Boudiaf, Hoel Kervadec, Ziko Imtiaz Masud, Pablo Piantanida, Ismail Ben Ayed, Jose Dolz CVPR 2021. [PDF] [CODE]
	Looking at the whole picture: constrained unsupervised anomaly segmentation Julio Silva Rodriguez, Valery Naranjo, Jose Dolz, BMVC 2021. [PDF] [CODE]
	Privacy Preserving for Medical Image Analysis via Non-Linear Deformation Proxy Bach Ngoc Kim, Jose Dolz,, Christian Desrosiers, Pierre-Marc Jodoin BMVC 2021. [PDF]
	Teach me to segment with mixed supervision: Confident students become masters. Jose Dolz,Christian Desrosiers, Ismail Ben Ayed IPMI 2021. [PDF] [CODE]
	Orthogonal Ensemble Networks for Biomedical Image Segmentation. Agostina Larrazabal, Cesar Martin, Jose Dolz, Enzo Ferrante MICCAI 2021, Oral Presentation. [PDF]
	Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty. Soufiane Belharbi, Jerome Rony, Jose Dolz, Ismail Ben Ayed, Luke McCaffrey, Eric Granger TMI 2021. [PDF] [CODE]
	Constrained Domain Adaptation for Image Segmentation. Mathilde Bateson, Jose Dolz,, Hoel Kervadec, Herve Lombaert, Ismail Ben Ayed TMI 2021. [PDF] [CODE]
	Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images. Bach Ngoc Kim, Jose Dolz, Pierre-Marc Jodoin, Christian Desrosiers TMI 2021. [PDF]
	Beyond pixel-wise supervision: semantic segmentation with higher-order shape descriptors. Hoel Kervadec, Houda Bahig, Laurent Letourneau-Guillon, Jose Dolz, Ismail Ben Ayed MIDL 2021, Oral Presentation (Best Paper Award). [PDF] [CODE]
	On the Texture Bias for Few-Shot CNN Segmentation. Reza Azad, Abdur Fayjie, Claude Kauffman, Ismail Ben Ayed, Marco Pedersoli, Jose Dolz WACV 2021. [PDF] [CODE]
	Information Maximization for Few-Shot Learning. Malik Boudiaf, Ziko Imtiaz Masud, Jérôme Rony, Jose Dolz, Pablo Piantanida, Ismail Ben Ayed NeurIPS 2020. [PDF] [CODE]
	Laplacian Regularized Few-Shot Learning. Imtiaz Ziko, Jose Dolz, Erig Granger, Ismail Ben Ayed ICML 2020. [PDF] [CODE]
	Source-Relaxed Domain Adaptation for Image Segmentation. Mathilde Bateson, Hoel Kervadec, Jose Dolz, Hervé Lombaert, Ismail Ben Ayed MICCAI 2020, Oral Presentation. [PDF] [CODE]
	Cost-Sensitive Regularization for Diabetic Retinopathy Grading from Eye Fundus Images . Adrian Galdran, Jose Dolz,, Hadi Chakor, Hervé Lombaert, Ismail Ben Ayed MICCAI 2020, Oral Presentation. [PDF] [CODE]
	Bounding boxes for weakly supervised segmentation: Global constraints get close to full supervision. Hoel Kervadec, Jose Dolz, Shanshan Wang, Eric Granger, Ismail Ben Ayed MIDL 2020. [PDF] [CODE]
	Multi-scale self-guided attention for medical image segmentation. Ashish Sinha, Jose Dolz IEEE JBHI 2019. [PDF] [CODE]
	Curriculum semi-supervised segmentation. Hoel Kervadec, Jose Dolz, Eric Granger, Ismail Ben Ayed MICCAI 2019. [PDF] [CODE]
	Constrained domain adaptation for segmentation. Mathilde Bateson, Jose Dolz, Hoel Kervadec, Herve Lombaert, Ismail Ben Ayed MICCAI 2019. [PDF] [CODE]
	Boundary loss for highly unbalanced segmentation. Hoel Kervadec, Jihene Bouchtiba, Christian Desrosiers, Eric Granger, Jose Dolz, Ismail Ben Ayed MIDL 2019, Oral Presentation (Best Paper Runner-up). [PDF] [CODE]
	Constrained-CNN losses for weakly supervised segmentation. Hoel Kervadec, Jose Dolz, Meng Tang, Eric Granger, Yuri Boykov, Ismail Ben Ayed MedIA 2019. [PDF] [CODE]
	HyperDenseNet: a hyper-densely connected CNN for multi-modal semantic segmentation. Jose Dolz, Karthik Gopinath, Jing Yuan, Herve Lombaert, Christian Desrosiers, Ismail Ben Ayed TMI 2018. [PDF] [CODE]
	Size-constraint loss for weakly supervised CNN segmentation. Hoel Kervadec, Jose Dolz, Meng Tang, Eric Granger, Yuri Boykov, Ismail Ben Ayed MIDL 2018, Oral Presentation. [PDF] [CODE]
	Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network. Jose Dolz, Ismail Ben Ayed, Jing Yuan, Christian Desrosiers ISBI 2018, Oral Presentation. [PDF]
	Unbiased Shape Compactness for Segmentation. Jose Dolz, Ismail Ben Ayed, Christian Desrosiers MICCAI 2017. [PDF]
	3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study. Jose Dolz, Christian Desrosiers, Ismail Ben Ayed NeuroImage 2017. [PDF] [CODE]
	DOPE: Distributed Optimization for Pairwise Energies. Jose Dolz, Ismail Ben Ayed, Christian Desrosiers CVPR 2017. [PDF]

Selected Awards

Best Paper Award: Towards foundation models and few-shot parameter-efficient fine-tuning for volumetric organ segmentation. 1st International Workshop on Foundation Models for General Medical AI

Outstanding Reviewer, ICCV 2023

Outstanding Reviewer, NeurIPS 2022

Outstanding Reviewer, CVPR 2022

Outstanding Reviewer, CVPR 2021

Best Paper Award - Winner: Beyond pixel-wise supervision: semantic segmentation with higher-order shape descriptors. MIDL 2021.

Outstanding Reviewer, ECCV 2020

Outstanding Reviewer, MICCAI 2020

Best Paper Runner-up: Boundary loss for highly unbalanced segmentation. MIDL 2019.

Academic Services

Area-Chair, ECCV: 2024

Area-Chair, MICCAI: 2021-2023

Area-Chair, MIDL: 2022-2024

Area-Chair, ICPR: 2022

Reviewer (journals):

- Medical Image Analysis (MedIA'19-Present)
- IEEE Transactions on Medical Imaging (TMI'18-Present)
- International Journal of Computer Vision (IJCV'19-Present)

Reviewer (conferences):

-Medical Image Computing and Computer Assisted Intervention (MICCAI'18-20)
-Computer Vision and Pattern Recognition (CVPR'19-Present)
-International Conference on Computer Vision (ICCV'19,'21,'23)
-European Conference on Computer Vision (ECCV'20,'22)
-Conference on Neural Information Processing Systems (NeurIPS'21-Present)
-AAAI Conference on Artificial Intelligence (AAAI'22)
-Information Processing in Medical Imaging (IPMI'22)
-International Conference on Learning Representations (ICLR'18,'19)

Students (Current)

Post-Doc

Julio Jose Silva Rodriguez. Visual Language pre-trained models in medical imaging (2023-)

PhD

Shambhavi Misra. Realistic evaluation of Continual Test-Time adaptation (2022-)
Sina Hajimiri. Generalized few-shot segmentation (2022-)
Balamurali Murugesan. Exploring uncertainty estimates in deep learning models (2022-)
Farzad Beizaee. Neonatal brain maturation assessment with deep multi-modal models (2021-)
Sukesh Adiga. Geometry of Medical Imaging Data in very Large Datasets (2019-)

MSc

Interns

Paul-Maxence Baraton. Conformal learning in deep neural networks (2022-)

Students (Former)

Post-Doc

Bingyuan Liu (2020-2023). R&D Amazon.

PhD

Hoel Kervadek (2017-2021). Post-Doc Erasmus Roterdam.
Bach Kim. (2019-2023)

MSc

Soumitri Chattopadhyay, MSc (MITACS Globalink) (2022). PhD student at UNC Chapel Hill.
Gaurav Patel, MSc (Remote Internship) (2020-2021). PhD student at Purdue University.
Julien Nicolas (2021-2023)PhD student at McGill University.
Bruce Cyusa Mukama (2019-2021).
Julie Galliere (2021). Eng. in Amadeus-Thales.
Jauffray Bruneton MSc (2019-2020). MBA student at California State University, Long Beach.
Tiphaine Diot, MSc (2019-2020).
Ashish Sinha, MSc (Remote Internship) (2019). Graduate Student in Computing Science. Simon Fraser University.
Aarush Gupta, MSc (Remote Internship) (2018). Research engineer at Rephrase.ai
Dakshit Agrawal, MSc (Remote Internship) (2018). MSc Student at Carnegie Mellon University
Arnab Mondal, MSc (MITACS Globalink) (2018). PhD Student at McGill University.
Jihene Bouchtiba, MSc (2017-2019).
Firas Bendhaou, MSc (2017-2019).

Interns

Julio Jose Silva Rodriguez (2021). Post-Doc ETS Montreal.
Agostina Larrazabal (2021)
Martin Van Waerebeke (2021-2022).
Alexandre Gautier (2021-2022).

Teaching

2023	Winter	MTI881:Deep Learning for Computer Vision
2022	Fall	MTI881:Deep Learning for Computer Vision
2022	Winter	LOG635:Intelligent Systems and Algorithms
2021	Fall	MTI881:Deep Learning for Computer Vision
2021	Winter	LOG635:Intelligent Systems and Algorithms
2020	Fall	GTI771:Advanced Machine learning
2020	Winter	LOG635:Intelligent Systems and Algorithms
2019	Fall	GTI770:Machine Learning