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Merge pull request #5 from AtlasAnalyticsLab/feature/publications-media-limits
feat: reformatting the layout of the publication, funding, and openin…
2 parents 093f99d + 8ae4018 commit bb2498a

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_data/publications.yml

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year: 2025
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status: "published"
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type: "article"
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journal: "Transactions on Machine Learning Research"
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journal: "Transactions on Machine Learning Research (TMLR 2025)"
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issn: "2835-8856"
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url: "https://openreview.net/pdf?id=e1aXaIXblQ"
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arxiv: "2506.15976"
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year: 2025
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status: "published"
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type: "inproceedings"
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booktitle: "Proceedings of the IEEE/CVF Conference on Computer Vision, Pattern Recognition (CVPR) 2025"
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booktitle: "Proceedings of the IEEE/CVF Conference on Computer Vision, Pattern Recognition (CVPR 2025)"
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url: "https://openaccess.thecvf.com/content/CVPR2025/html/Zhang_2DMamba_Efficient_State_Space_Model_for_Image_Representation_with_Applications_CVPR_2025_paper.html"
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arxiv: "2412.00678"
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github: "https://github.com/AtlasAnalyticsLab/2DMamba"
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year: 2025
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status: "published"
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type: "inproceedings"
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booktitle: "International Conference on Learning Representations (ICLR) 2025"
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booktitle: "International Conference on Learning Representations (ICLR 2025)"
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url: "https://openreview.net/pdf?id=puTxuiK2qO"
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arxiv: "2405.16397"
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github: "https://github.com/AtlasAnalyticsLab/AdaFisher"
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year: 2024
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status: "published"
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type: "inproceedings"
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booktitle: "Proceedings of the IEEE/CVF Conference on Computer Vision, Pattern Recognition (CVPR) 2024"
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booktitle: "Proceedings of the IEEE/CVF Conference on Computer Vision, Pattern Recognition (CVPR 2024)"
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url: "https://openaccess.thecvf.com/content/CVPR2024W/CVMI/html/Nasiri-Sarvi_Vim4Path_Self-Supervised_Vision_Mamba_for_Histopathology_Images_CVPRW_2024_paper.html"
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arxiv: "2404.13222"
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github: "https://github.com/AtlasAnalyticsLab/Vim4Path"

_includes/publication-item.html

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{%- comment -%}
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Publication card partial:
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- Displays a thumbnail column (defaults to the lab logo when no list_image is provided).
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- Renders venue metadata and resource links pulled from _data/publications.yml.
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Publication list entry rendered in a simple two-column layout (image + text).
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{%- endcomment -%}
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{% assign entry = include.entry | default: empty %}
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{% assign include_year = include.include_year | default: false %}
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{% assign item_id = entry.id | default: entry.title | slugify %}
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{% assign list_image = entry.list_image %}
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{% assign list_image = 'images/logopic/group_logo_medium.png' %}
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{% endif %}
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{% assign meta_parts = '' | split: '' %}
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{% comment %}
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List of possible venue fields in order of preference.
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{%- endcomment -%}
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{% assign venue = entry.journal | default: entry.booktitle | default: entry.publisher | default: entry.school %}
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{% if venue %}
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{% assign meta_parts = meta_parts | push: venue %}
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{% endif %}
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{% if entry.series %}
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{% assign meta_parts = meta_parts | push: entry.series %}
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{% endif %}
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{% assign volume_part = '' %}
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{% if entry.volume %}
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{% assign volume_part = 'Vol. ' | append: entry.volume %}
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{% endif %}
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{% if entry.number %}
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{% assign number_part = 'No. ' | append: entry.number %}
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{% if volume_part %}
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{% assign volume_part = volume_part | append: ', ' | append: number_part %}
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{% else %}
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{% assign volume_part = number_part %}
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{% endif %}
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{% endif %}
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{% if volume_part %}
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{% assign meta_parts = meta_parts | push: volume_part %}
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{% endif %}
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{% if entry.pages %}
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{% assign meta_parts = meta_parts | push: 'pp. ' | append: entry.pages %}
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{% endif %}
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{% if entry.month %}
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{% assign meta_parts = meta_parts | push: entry.month %}
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{% endif %}
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{% if include_year and entry.year %}
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{% assign meta_parts = meta_parts | push: entry.year %}
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{% endif %}
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{% capture meta_string %}{{ meta_parts | join: ' · ' }}{% endcapture %}
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{% assign meta_string = meta_string | strip %}
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{% assign link_count = 0 %}
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{% if entry.url %}{% assign link_count = link_count | plus: 1 %}{% endif %}
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{% if entry.arxiv %}{% assign link_count = link_count | plus: 1 %}{% endif %}
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{% if entry.github %}{% assign link_count = link_count | plus: 1 %}{% endif %}
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{% if entry.doi %}{% assign link_count = link_count | plus: 1 %}{% endif %}
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{% if entry.video %}{% assign link_count = link_count | plus: 1 %}{% endif %}
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{% if entry.poster %}{% assign link_count = link_count | plus: 1 %}{% endif %}
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<li class="publication-item" id="{{ item_id }}">
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<div class="publication-card publication-card--with-media">
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<div class="publication-card__media">
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<div class="publication-item" id="{{ item_id }}">
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<div class="publication-entry">
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<div class="publication-entry__image">
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<img src="{{ list_image | relative_url }}" alt="Illustration for {{ entry.title | escape }}" loading="lazy">
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</div>
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<div class="publication-card__body">
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<div class="publication-title">{{ entry.title }}</div>
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<div class="publication-entry__details">
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<p class="publication-entry__title"><strong>{{ entry.title }}</strong></p>
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{% if entry.authors %}
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<div class="publication-authors">{{ entry.authors }}</div>
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<p class="publication-entry__authors">{{ entry.authors }}</p>
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{% endif %}
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{% if meta_string != '' %}
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<div class="publication-meta">{{ meta_string }}</div>
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{% if venue %}
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<p class="publication-entry__venue"><em>{{ venue }}</em></p>
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{% endif %}
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{% if entry.note %}
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<div class="publication-note">{{ entry.note }}</div>
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<p class="publication-entry__note">{{ entry.note }}</p>
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{% endif %}
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{% if link_count > 0 %}
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<p class="publication-entry__links">
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{% if entry.url %}
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<a href="{{ entry.url }}">[LINK]</a>
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{% endif %}
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{% if entry.arxiv %}
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<a href="https://arxiv.org/abs/{{ entry.arxiv }}">[ARXIV]</a>
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{% endif %}
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{% if entry.github %}
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<a href="{{ entry.github }}">[CODE]</a>
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{% endif %}
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{% if entry.doi %}
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<a href="https://doi.org/{{ entry.doi }}">[DOI]</a>
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{% endif %}
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{% if entry.video %}
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<a href="{{ entry.video }}">[VIDEO]</a>
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{% endif %}
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{% if entry.poster %}
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<a href="{{ entry.poster }}">[POSTER]</a>
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{% endif %}
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</p>
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{% endif %}
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<div class="publication-links">
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{% assign link_count = 0 %}
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{%- comment -%}
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Publication links in consistent order:
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1. Link (project/paper website)
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2. arXiv
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3. GitHub
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4. DOI
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5. PDF
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6. Video
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7. Poster
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{%- endcomment -%}
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{% if entry.url %}
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{% assign link_count = link_count | plus: 1 %}
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<a class="pub-link" href="{{ entry.url }}">Link</a>
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{% endif %}
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{% if entry.arxiv %}
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{% assign link_count = link_count | plus: 1 %}
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<a class="pub-link" href="https://arxiv.org/abs/{{ entry.arxiv }}">arXiv</a>
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{% endif %}
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{% if entry.github %}
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{% assign link_count = link_count | plus: 1 %}
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<a class="pub-link" href="{{ entry.github }}">GitHub</a>
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{% endif %}
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{% if entry.doi %}
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{% assign link_count = link_count | plus: 1 %}
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<a class="pub-link" href="https://doi.org/{{ entry.doi }}">DOI</a>
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{% endif %}
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{% if entry.video %}
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{% assign link_count = link_count | plus: 1 %}
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<a class="pub-link" href="{{ entry.video }}">Video</a>
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{% endif %}
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{% if entry.poster %}
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{% assign link_count = link_count | plus: 1 %}
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<a class="pub-link" href="{{ entry.poster }}">Poster</a>
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{% endif %}
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{% if link_count == 0 %}
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<span class="pub-link placeholder">Links coming soon</span>
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{% endif %}
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</div>
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</div>
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</div>
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</li>
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</div>

_pages/funding.md

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<div class="row g-4 align-items-center justify-content-center my-5" markdown="0">
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<div class="col-12 col-sm-6 col-md-4 text-center">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Concordia_University.png" class="img-fluid" style="max-width: 100%; width: 100%;">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Concordia_University.png" class="img-fluid funding-logo">
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</div>
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<div class="col-12 col-sm-6 col-md-4 text-center">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/NSERC_CRSNG.png" class="img-fluid" style="max-width: 100%; width: 100%;">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/NSERC_CRSNG.png" class="img-fluid funding-logo">
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</div>
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<div class="col-12 col-sm-6 col-md-4 text-center">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/FRQNT.png" class="img-fluid" style="max-width: 100%; width: 100%;">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/FRQNT.png" class="img-fluid funding-logo">
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</div>
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<div class="col-12 col-sm-6 col-md-4 text-center">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Amazon_Research_Awards.png" class="img-fluid" style="max-width: 100%; width: 100%;">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Amazon_Research_Awards.png" class="img-fluid funding-logo">
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</div>
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<div class="col-12 col-sm-6 col-md-4 text-center">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/CFI.png" class="img-fluid" style="max-width: 100%; width: 100%;">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/CFI.png" class="img-fluid funding-logo">
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</div>
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<div class="col-12 col-sm-6 col-md-4 text-center">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/IRICoR.png" class="img-fluid" style="max-width: 100%; width: 100%;">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/IRICoR.png" class="img-fluid funding-logo">
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</div>
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<div class="col-12 col-sm-6 col-md-4 text-center">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Digital_Research_Alliance.png" class="img-fluid" style="max-width: 100%; width: 100%;">
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<img src="{{ site.url }}{{ site.baseurl }}/images/logopic/Digital_Research_Alliance.png" class="img-fluid funding-logo">
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</div>
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</div>

_pages/openings.md

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---
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We seek high-caliber candidates with strong academic records (high CGPAs), research experience in medical imaging or computer vision, publications in top-tier AI/ML venues (CVPR, NeurIPS, ICLR, ICML, TMLR), and hands-on experience with PyTorch and deep learning implementation.
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We are currently recruiting for the following positions:
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1. **Fully Funded PhD Position in AI for Computational Pathology and Medicine** - Co-supervised with [**Prof. Christopher Pal**](https://scholar.google.com/citations?hl=en&user=1ScWJOoAAAAJ&view_op=list_works&sortby=pubdate)
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- See instructions and details in [PDF]({{ site.url }}{{ site.baseurl }}/assets/openings/PhD_Hiring_Post_2026_Pathology@McGill%20(CPv2-MSHv2).pdf)
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2. **Fully Funded PhD Position in Diffusion Generative Modeling and Deep Learning for Medical Imaging (Radiology & Pathology)** - Co-supervised with [**Prof. Hassan Rivaz**](https://scholar.google.com/citations?hl=zh-CN&user=FWDzqVUAAAAJ&view_op=list_works&sortby=pubdate)
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- See instructions and details in [PDF]({{ site.url }}{{ site.baseurl }}/assets/openings/Hiring_Post_Diffusion_Generatrive_Modeling_2026_HRv1_MSHv2.pdf)
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---
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## Funding / Fellowships
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Applicants with **external scholarships or fellowships** are encouraged and fully supported:
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- **[FRQNT Graduate Scholarships](https://frq.gouv.qc.ca/en/open-competitions/)** (Unrestricted)
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- **[NSERC](https://www.nserc-crsng.gc.ca/index_eng.asp)** (Canadian PR or citizen)
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- **[Pierre Arbour Foundation](https://www.fondationarbour.com/en/bourses-d-etudes-doctoract-phd-dba/)** (Unrestricted)
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We support candidates in preparing fellowship applications.
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We seek high-caliber candidates with strong academic records (high CGPAs), research experience in medical imaging or computer vision, publications in top-tier AI/ML venues (CVPR, NeurIPS, ICLR, ICML, TMLR), and hands-on experience with PyTorch and deep learning implementation. We are currently recruiting for the following positions:
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1. **Fully Funded PhD Position in AI for Computational Pathology and Medicine** - Co-supervised with [**Prof. Christopher Pal**](https://scholar.google.com/citations?hl=en&user=1ScWJOoAAAAJ&view_op=list_works&sortby=pubdate). See instructions and details in [PDF]({{ site.url }}{{ site.baseurl }}/assets/openings/PhD_Hiring_Post_2026_Pathology@McGill%20(CPv2-MSHv2).pdf)
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2. **Fully Funded PhD Position in Diffusion Generative Modeling and Deep Learning for Medical Imaging (Radiology & Pathology)** - Co-supervised with [**Prof. Hassan Rivaz**](https://scholar.google.com/citations?hl=zh-CN&user=FWDzqVUAAAAJ&view_op=list_works&sortby=pubdate). See instructions and details in [PDF]({{ site.url }}{{ site.baseurl }}/assets/openings/Hiring_Post_Diffusion_Generatrive_Modeling_2026_HRv1_MSHv2.pdf)

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