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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>Eric Zimmermann</title>
<meta
name="description"
content="Eric Zimmermann is a machine learning researcher working on biomedical machine learning, representation learning, and multimodal systems."
>
<link rel="stylesheet" href="styles.css">
</head>
<body>
<nav class="site-nav" aria-label="Site navigation">
<div class="container">
<div class="site-links">
<button type="button" data-section-target="about" aria-pressed="true">
About
</button>
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Research
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</div>
</div>
</nav>
<main class="container">
<section id="about" class="section" data-section-panel="about">
<header class="page-header">
<h1>Eric Zimmermann</h1>
<p>
Senior Applied Scientist,
<a href="https://www.microsoft.com/en-us/research/theme/biomedical-ml/">
Biomedical ML</a>
</p>
</header>
<aside class="profile" aria-label="Profile links">
<img class="profile-photo" src="assets/profile.jpg" alt="Eric Zimmermann">
<p>Biomedical machine learning</p>
<p>Representation learning</p>
<p>Multimodal systems</p>
<ul class="profile-links">
<li>
<a href="mailto:ezimmermann@microsoft.com">
<svg class="icon icon-stroke" aria-hidden="true" viewBox="0 0 24 24">
<path d="M4.75 5.5h14.5c.69 0 1.25.56 1.25 1.25v10.5c0 .69-.56 1.25-1.25 1.25H4.75c-.69 0-1.25-.56-1.25-1.25V6.75c0-.69.56-1.25 1.25-1.25Z"/>
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<span>ezimmermann@microsoft.com</span>
</a>
</li>
<li>
<a href="https://github.com/EricZimmermann">
<svg class="icon icon-fill" aria-hidden="true" viewBox="0 0 24 24">
<path d="M12 .3C5.37.3 0 5.67 0 12.3c0 5.3 3.44 9.8 8.21 11.39.6.11.82-.26.82-.58v-2.04c-3.34.73-4.04-1.61-4.04-1.61-.55-1.39-1.33-1.76-1.33-1.76-1.09-.74.08-.73.08-.73 1.2.09 1.84 1.24 1.84 1.24 1.07 1.83 2.81 1.3 3.49.99.11-.77.42-1.3.76-1.6-2.67-.31-5.47-1.34-5.47-5.93 0-1.31.47-2.38 1.24-3.22-.13-.3-.54-1.52.11-3.18 0 0 1.01-.32 3.3 1.23.96-.27 1.99-.4 3.01-.4s2.05.13 3.01.4c2.29-1.55 3.3-1.23 3.3-1.23.65 1.66.24 2.88.12 3.18.77.84 1.23 1.91 1.23 3.22 0 4.61-2.8 5.62-5.48 5.92.43.37.82 1.1.82 2.22v3.3c0 .32.21.69.82.58A12.01 12.01 0 0 0 24 12.3C24 5.67 18.63.3 12 .3Z"/>
</svg>
<span>github.com/EricZimmermann</span>
</a>
</li>
<li>
<a href="https://scholar.google.com/citations?user=ke-GE6kAAAAJ&hl=en&oi=ao">
<svg class="icon icon-fill" aria-hidden="true" viewBox="0 0 24 24">
<path d="M5.24 13.77 0 9.5 12 0l12 9.5-5.24 4.27C17.55 11.25 14.98 9.5 12 9.5s-5.55 1.75-6.76 4.27Z"/>
<path d="M12 10.5a6 6 0 1 0 0 12 6 6 0 0 0 0-12Z"/>
</svg>
<span>Google Scholar</span>
</a>
</li>
</ul>
</aside>
<div class="about-copy">
<p>
I am a Senior Applied Scientist at
<a href="https://www.microsoft.com/en-us/research/lab/microsoft-research-new-england/">
Microsoft Research New England</a>. My work focuses on
machine learning methods for scientific and biomedical data, with
interests in biomedical machine learning, representation learning,
and multimodal systems.
</p>
<p>
Much of my recent research has focused on computational
histopathology and fluorescent microscopy at scale. This includes
work published in Nature
Medicine on clinical grade cancer detection.
</p>
<p>
Previously, I worked at Sama on data curation and dataset quality,
and at CAE as an electrical system designer for full-flight
simulators.
</p>
<p>
I completed my M.Sc. and B.Eng. in Electrical and Computer
Engineering at McGill University and
<a href="https://mila.quebec/en/">Mila</a>, where I worked in the
<a href="https://cim.mcgill.ca/~pvg/">
Probabilistic Vision Group</a> under Tal Arbel. My research
focused on self-supervised learning, alignment, and representation
geometry, with applications to brain MRI analysis for detecting and
predicting disease progression in multiple sclerosis.
</p>
<p>
I am always happy to hear from people interested in related research
or potential collaborations; the best way to reach me is ezimmermann
at microsoft dot com.
</p>
<p>
Outside of work, I enjoy hiking, video games, and excessive amounts
of coffee.
</p>
</div>
</section>
<section id="research" class="section" data-section-panel="research" hidden>
<h2>Research</h2>
<div class="research-lede">
<p>
My research focuses on self-supervised and multimodal learning for
scientific and biomedical data. I am especially interested in
methods that learn useful representations from large, heterogeneous
datasets and transfer across tasks, institutions, scales, and
measurement modalities. Current research interests:
</p>
<ul class="interest-list">
<li>
Applications of self-supervised learning to biomedical problems,
including histopathology, fluorescence microscopy, and single-cell
RNA sequencing.
</li>
<li>
Understanding the theory and geometry of representation learning.
</li>
<li>
Multimodal modeling and integration across heterogeneous data
sources.
</li>
</ul>
</div>
<h3>Selected work</h3>
<ol class="publication-list selected-publications">
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2512.19605">
KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised
Learning
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Harley Wiltzer, Justin Szeto,
David Alvarez-Melis, and Lester Mackey.
</p>
<p class="publication-venue">arXiv:2512.19605, 2025.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://www.nature.com/articles/s41591-024-03141-0">
A foundation model for clinical-grade computational pathology
and rare cancers detection
</a>
</p>
<p class="publication-authors">
Eugene Vorontsov, Alican Bozkurt, Adam Casson, George
Shaikovski, Michal Zelechowski, Kristen Severson,
<strong>Eric Zimmermann</strong>, James Hall, Neil Tenenholtz,
Nicolo Fusi, Ellen Yang, Philippe Mathieu, Alexander van Eck,
Donghun Lee, Julian Viret, Eric Robert, Yi Kan Wang, Jeremy D.
Kunz, Matthew C. H. Lee, Jan H. Bernhard, Ran A. Godrich, Gerard
Oakley, Ewan Millar, Matthew Hanna, Hannah Wen, Juan A. Retamero,
William A. Moye, Razik Yousfi, Christopher Kanan, David S.
Klimstra, Brandon Rothrock, Siqi Liu, and Thomas J. Fuchs.
</p>
<p class="publication-venue">
<em>Nature Medicine</em> 30(10), 2924-2935, 2024.
</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://www.nature.com/articles/s41591-026-04521-4">
End-to-end multimodal pathology foundation model with clinical
dialogue
</a>
</p>
<p class="publication-authors">
Eugene Vorontsov, George Shaikovski, Adam Casson, Julian Viret,
<strong>Eric Zimmermann</strong>, Neil Tenenholtz, Yi Kan Wang,
Jan H. Bernhard, Ran A. Godrich, Juan A. Retamero, Jinru Shia,
Mithat Gonen, Martin R. Weiser, David S. Klimstra, Razik Yousfi,
Nicolo Fusi, Thomas J. Fuchs, Kristen Severson, and Siqi Liu.
</p>
<p class="publication-venue"><em>Nature Medicine</em>, 2026.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2408.00738">
Virchow2: Scaling Self-Supervised Mixed Magnification Models in
Pathology
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Eugene Vorontsov, Julian Viret,
Adam Casson, Michal Zelechowski, George Shaikovski, Neil
Tenenholtz, James Hall, David Klimstra, Razik Yousfi, Thomas
Fuchs, Nicolo Fusi, Siqi Liu, and Kristen Severson.
</p>
<p class="publication-venue">arXiv:2408.00738, 2024.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2405.10254">
PRISM: A multi-modal generative foundation model for slide-level
histopathology
</a>
</p>
<p class="publication-authors">
George Shaikovski, Adam Casson, Kristen Severson,
<strong>Eric Zimmermann</strong>, Yi Kan Wang, Jeremy D. Kunz,
Juan A. Retamero, Gerard Oakley, David Klimstra, Christopher
Kanan, Matthew Hanna, Michal Zelechowski, Julian Viret, Neil
Tenenholtz, James Hall, Nicolo Fusi, Razik Yousfi, Peter
Hamilton, William A. Moye, Eugene Vorontsov, Siqi Liu, and Thomas
J. Fuchs.
</p>
<p class="publication-venue">arXiv:2405.10254, 2024.</p>
</li>
</ol>
<h3>Publications</h3>
<ol class="publication-list">
<li class="publication">
<p class="publication-title">
<a href="https://www.nature.com/articles/s41591-026-04521-4">
End-to-end multimodal pathology foundation model with clinical
dialogue
</a>
</p>
<p class="publication-authors">
Eugene Vorontsov, George Shaikovski, Adam Casson, Julian Viret,
<strong>Eric Zimmermann</strong>, Neil Tenenholtz, Yi Kan Wang,
Jan H. Bernhard, Ran A. Godrich, Juan A. Retamero, Jinru Shia,
Mithat Gonen, Martin R. Weiser, David S. Klimstra, Razik Yousfi,
Nicolo Fusi, Thomas J. Fuchs, Kristen Severson, and Siqi Liu.
</p>
<p class="publication-venue"><em>Nature Medicine</em>, 2026.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2606.28395">
JASPR: Joint Spatial Representation learning of histology and
spatial genomics for improved virtual genomic screening and
clinical prognostication
</a>
</p>
<p class="publication-authors">
Marija Pizurica, <strong>Eric Zimmermann</strong>, Neil
Tenenholtz, James Hall, Olivier Gevaert, Ava P. Amini, Lorin
Crawford, and Kristen A. Severson.
</p>
<p class="publication-venue">arXiv:2606.28395, 2026.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://doi.org/10.64898/2026.06.01.729395">
Vermeer: Autoregressive generative modeling of microscopy
predicts protein localization
</a>
</p>
<p class="publication-authors">
Sandeep Kambhampati, <strong>Eric Zimmermann</strong>, Emre
Hayir, Kevin K. Yang, Fei Chen, and Alex X. Lu.
</p>
<p class="publication-venue">
bioRxiv, 2026.06.01.729395, 2026.
</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://www.cell.com/cell/fulltext/S0092-8674%2826%2900328-4">
Tackling the complexity of cancer with generative models
</a>
</p>
<p class="publication-authors">
Ashley Mae Conard, Madeline Hughes, James Hall, Neil Tenenholtz,
<strong>Eric Zimmermann</strong>, Lorin Crawford, Ava P. Amini,
and Kristen Severson.
</p>
<p class="publication-venue">
<em>Cell</em> 189(8), 2218-2231, 2026.
</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2603.00193">
Multimodal Alignment Improves Generalizability of Genomic
Biomarker Prediction in Computational Pathology
</a>
</p>
<p class="publication-authors">
Ekaterina Redekop, <strong>Eric Zimmermann</strong>, Ava P.
Amini, Alex X. Lu, Neil Tenenholtz, James Brian Hall, Lorin
Crawford, and Kristen A. Severson.
</p>
<p class="publication-venue">arXiv:2603.00193, 2026.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2602.22176">
Mixed Magnification Aggregation for Generalizable Region-Level
Representations in Computational Pathology
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Julian Viret, Michal
Zelechowski, James Brian Hall, Neil Tenenholtz, Adam Casson,
George Shaikovski, Eugene Vorontsov, Siqi Liu, and Kristen A.
Severson.
</p>
<p class="publication-venue">arXiv:2602.22176, 2026.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://doi.org/10.64898/2026.02.23.707420">
Beyond alignment: synergistic integration is required for
multimodal cell foundation models
</a>
</p>
<p class="publication-authors">
T. Richter, <strong>E. Zimmermann</strong>, J. Hall, F. J.
Theis, S. Raghavan, P. S. Winter, A. P. Amini, and L. Crawford.
</p>
<p class="publication-venue">bioRxiv, 2026.02.23.707420, 2026.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2512.19605">
KerJEPA: Kernel Discrepancies for Euclidean Self-Supervised
Learning
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Harley Wiltzer, Justin Szeto,
David Alvarez-Melis, and Lester Mackey.
</p>
<p class="publication-venue">arXiv:2512.19605, 2025.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2408.00738">
Virchow2: Scaling Self-Supervised Mixed Magnification Models in
Pathology
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Eugene Vorontsov, Julian Viret,
Adam Casson, Michal Zelechowski, George Shaikovski, Neil
Tenenholtz, James Hall, David Klimstra, Razik Yousfi, Thomas
Fuchs, Nicolo Fusi, Siqi Liu, and Kristen Severson.
</p>
<p class="publication-venue">arXiv:2408.00738, 2024.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2405.10254">
PRISM: A multi-modal generative foundation model for slide-level
histopathology
</a>
</p>
<p class="publication-authors">
George Shaikovski, Adam Casson, Kristen Severson,
<strong>Eric Zimmermann</strong>, Yi Kan Wang, Jeremy D. Kunz,
Juan A. Retamero, Gerard Oakley, David Klimstra, Christopher
Kanan, Matthew Hanna, Michal Zelechowski, Julian Viret, Neil
Tenenholtz, James Hall, Nicolo Fusi, Razik Yousfi, Peter
Hamilton, William A. Moye, Eugene Vorontsov, Siqi Liu, and Thomas
J. Fuchs.
</p>
<p class="publication-venue">arXiv:2405.10254, 2024.</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2405.01688">
Adapting self-supervised learning for computational pathology
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Neil Tenenholtz, James Hall,
George Shaikovski, Michal Zelechowski, Adam Casson, Fausto
Milletari, Julian Viret, Eugene Vorontsov, Siqi Liu, and Kristen
Severson.
</p>
<p class="publication-venue">
DCA in MI Workshop, CVPR 2024; arXiv:2405.01688, 2024.
</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://www.nature.com/articles/s41591-024-03141-0">
A foundation model for clinical-grade computational pathology
and rare cancers detection
</a>
</p>
<p class="publication-authors">
Eugene Vorontsov, Alican Bozkurt, Adam Casson, George
Shaikovski, Michal Zelechowski, Kristen Severson,
<strong>Eric Zimmermann</strong>, James Hall, Neil Tenenholtz,
Nicolo Fusi, Ellen Yang, Philippe Mathieu, Alexander van Eck,
Donghun Lee, Julian Viret, Eric Robert, Yi Kan Wang, Jeremy D.
Kunz, Matthew C. H. Lee, Jan H. Bernhard, Ran A. Godrich, Gerard
Oakley, Ewan Millar, Matthew Hanna, Hannah Wen, Juan A. Retamero,
William A. Moye, Razik Yousfi, Christopher Kanan, David S.
Klimstra, Brandon Rothrock, Siqi Liu, and Thomas J. Fuchs.
</p>
<p class="publication-venue">
<em>Nature Medicine</em> 30(10), 2924-2935, 2024.
</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2311.02709">
Benchmarking a benchmark: How reliable is MS-COCO?
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Justin Szeto, Jerome Pasquero,
and Frederic Ratle.
</p>
<p class="publication-venue">
DataComp Workshop, ICCV 2023; arXiv:2311.02709, 2023.
</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://arxiv.org/abs/2311.02707">
An empirical study of uncertainty in polygon annotation and the
impact of quality assurance
</a>
</p>
<p class="publication-authors">
<strong>Eric Zimmermann</strong>, Justin Szeto, and Frederic
Ratle.
</p>
<p class="publication-venue">
DataComp Workshop, ICCV 2023; arXiv:2311.02707, 2023.
</p>
</li>
<li class="publication">
<p class="publication-title">
<a href="https://hal.inria.fr/hal-03358968v2">
Consensus learning with multi-rater labels for segmenting and
detecting new lesions
</a>
</p>
<p class="publication-authors">
Brennan Nichyporuk, Kirill Vasilevski, Anjun Hu, Chelsea
Myers-Colet, Jillian Cardinell, Justin Szeto, Jean-Pierre Falet,
<strong>Eric Zimmermann</strong>, Julien Schroeter, Douglas L.
Arnold, and Tal Arbel.
</p>
<p class="publication-venue">
<em>MSSEG-2 challenge proceedings: Multiple sclerosis new lesions
segmentation challenge using a data management and processing
infrastructure</em>, 2021.
</p>
</li>
</ol>
</section>
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