Mohammad Havaei

4.8k total citations · 1 hit paper
16 papers, 2.5k citations indexed

About

Mohammad Havaei is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Mohammad Havaei has authored 16 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 9 papers in Artificial Intelligence and 2 papers in Cognitive Neuroscience. Recurrent topics in Mohammad Havaei's work include Domain Adaptation and Few-Shot Learning (7 papers), Multimodal Machine Learning Applications (5 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Mohammad Havaei is often cited by papers focused on Domain Adaptation and Few-Shot Learning (7 papers), Multimodal Machine Learning Applications (5 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). Mohammad Havaei collaborates with scholars based in Canada, Iran and China. Mohammad Havaei's co-authors include Pierre‐Marc Jodoin, Hugo Larochelle, Yoshua Bengio, Aaron Courville, Axel Davy, David Warde-Farley, Chris Pal, Qicheng Lao, Philippe Poulin and Gabriel Chartrand and has published in prestigious journals such as Pattern Recognition, IEEE Transactions on Neural Networks and Learning Systems and Machine Learning.

In The Last Decade

Mohammad Havaei

16 papers receiving 2.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Brain tumor segmentation with Deep Neural Networks

2016 2.1k citations Mohammad Havaei, Axel Davy et al. Medical Image Analysis profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mohammad Havaei Canada	13	1.6k	1.3k	789	733	306	16	2.5k
Axel Davy France	9	1.4k 0.9×	1.2k 0.9×	642 0.8×	712 1.0×	313 1.0×	16	2.3k
Sérgio Pereira Portugal	19	1.6k 1.0×	1.4k 1.1×	892 1.1×	1.2k 1.6×	356 1.2×	34	3.0k
Carlos A. Silva Portugal	20	1.6k 1.0×	1.4k 1.1×	836 1.1×	1.1k 1.5×	377 1.2×	55	3.1k
Adriano Pinto Portugal	8	1.3k 0.8×	1.3k 1.0×	561 0.7×	614 0.8×	286 0.9×	10	2.1k
Chris Pal United States	19	2.6k 1.6×	1.3k 0.9×	1.3k 1.7×	802 1.1×	440 1.4×	41	4.1k
Vishwesh Nath United States	17	1.1k 0.7×	470 0.4×	703 0.9×	1.3k 1.8×	384 1.3×	50	2.6k
Tal Arbel Canada	25	1.5k 0.9×	355 0.3×	661 0.8×	987 1.3×	394 1.3×	97	2.8k
Deepak Ranjan Nayak India	26	723 0.5×	540 0.4×	908 1.2×	760 1.0×	122 0.4×	74	2.0k
Konstantinos Kamnitsas United Kingdom	17	1.8k 1.1×	971 0.7×	991 1.3×	1.5k 2.1×	637 2.1×	32	3.8k
Assaf Hoogi United States	14	600 0.4×	451 0.3×	841 1.1×	886 1.2×	243 0.8×	24	1.8k

Countries citing papers authored by Mohammad Havaei

Since Specialization

Citations

This map shows the geographic impact of Mohammad Havaei's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mohammad Havaei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Havaei more than expected).

Fields of papers citing papers by Mohammad Havaei

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Havaei. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mohammad Havaei. The network helps show where Mohammad Havaei may publish in the future.

Co-authorship network of co-authors of Mohammad Havaei

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Havaei. A scholar is included among the top collaborators of Mohammad Havaei based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mohammad Havaei. Mohammad Havaei is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

1.

Kahou, Samira Ebrahimi, et al.. (2025). Source-free domain adaptation requires penalized diversity. Machine Learning. 114(10). 1 indexed citations

2.

Azarnoush, Hamed, et al.. (2022). Stain transfer using Generative Adversarial Networks and disentangled features. Computers in Biology and Medicine. 142. 105219–105219. 18 indexed citations

3.

Desrosiers, Christian, et al.. (2022). Revisiting Learnable Affines for Batch Norm in Few-Shot Transfer Learning. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 9099–9108. 16 indexed citations

4.

Havaei, Mohammad, et al.. (2021). Conditional generation of medical images via disentangled adversarial inference. Medical Image Analysis. 72. 102106–102106. 14 indexed citations

5.

Lao, Qicheng, et al.. (2021). Hypothesis Disparity Regularized Mutual Information Maximization. Proceedings of the AAAI Conference on Artificial Intelligence. 35(9). 8243–8251. 15 indexed citations

6.

Lao, Qicheng, et al.. (2021). A Two-Stream Continual Learning System With Variational Domain-Agnostic Feature Replay. IEEE Transactions on Neural Networks and Learning Systems. 33(9). 4466–4478. 15 indexed citations

7.

Lao, Qicheng, et al.. (2021). FoCL: Feature-oriented continual learning for generative models. Pattern Recognition. 120. 108127–108127. 12 indexed citations

8.

Havaei, Mohammad, et al.. (2020). CAGNet: Content-Aware Guidance for Salient Object Detection. Pattern Recognition. 103. 107303–107303. 94 indexed citations

9.

Lao, Qicheng, et al.. (2019). Dual Adversarial Inference for Text-to-Image Synthesis. 7566–7575. 19 indexed citations

10.

Havaei, Mohammad, et al.. (2019). DFNet: Discriminative feature extraction and integration network for salient object detection. Engineering Applications of Artificial Intelligence. 89. 103419–103419. 28 indexed citations

11.

Havaei, Mohammad, et al.. (2018). Learning to Learn with Conditional Class Dependencies. International Conference on Learning Representations. 27 indexed citations

12.

Havaei, Mohammad, Gabriel Chartrand, Thomas L. Vincent, et al.. (2018). Attentive Task-Agnostic Meta-Learning for Few-Shot Text Classification. 15 indexed citations

13.

Havaei, Mohammad, Axel Davy, David Warde-Farley, et al.. (2016). Brain tumor segmentation with Deep Neural Networks. Medical Image Analysis. 35. 18–31. 2102 indexed citations breakdown →

14.

Havaei, Mohammad, Hugo Larochelle, Philippe Poulin, & Pierre‐Marc Jodoin. (2015). Within-brain classification for brain tumor segmentation. International Journal of Computer Assisted Radiology and Surgery. 11(5). 777–788. 52 indexed citations

15.

Havaei, Mohammad, Pierre‐Marc Jodoin, & Hugo Larochelle. (2014). Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification. 556–561. 61 indexed citations

16.

Havaei, Mohammad, et al.. (2013). A novel plane extraction approach using supervised learning. Machine Vision and Applications. 24(6). 1229–1237. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact