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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Eric Cramer - MD-PhD Candidate in Computational Oncology</title>
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.nav-links { display: none; }
body::before { display: none; }
}
</style>
</head>
<body>
<header>
<nav>
<div class="logo">Eric Cramer</div>
<ul class="nav-links">
<li><a href="#about">About</a></li>
<li><a href="#research">Research</a></li>
<li><a href="#publications">Publications</a></li>
<li><a href="#contact">Contact</a></li>
<li><a href="cv-academic.pdf" target="_blank">CV</a></li>
</ul>
</nav>
</header>
<section class="hero">
<canvas id="networkCanvas" aria-hidden="true"></canvas>
<div class="hero-content">
<h1>Eric Cramer</h1>
<p class="subtitle">MD-PhD Candidate · Computational Oncology</p>
<p class="tagline">
Bridging <span class="accent-text">medicine</span>, <span class="accent-text">mathematical modeling</span>,
and <span class="accent-text">machine learning</span> to advance precision oncology and
transform cancer treatment through data-driven insights.
</p>
</div>
<div class="hero-photo">
<img class="profile-photo" src="profile.png" alt="Eric Cramer">
</div>
</section>
<section id="about">
<h2>About</h2>
<div class="about-content">
<div class="about-text">
<p>
I am an MD-PhD candidate in the Medical Scientist Training Program (MSTP) at Oregon Health & Science
University. My PhD research in Biomedical Engineering focuses on mathematical and computational modeling
for precision oncology using simulation and deep learning, advised by Dr. Young Hwan Chang and Dr. Laura Heiser.
</p>
<p>
My work spans agent-based modeling of the tumor microenvironment, computational analysis of multiplexed
tissue imaging, and machine learning for cancer biology. I aim to develop tools that translate quantitative
insights into clinically actionable strategies for cancer patients.
</p>
<p>
Before OHSU, I was a Data Analyst at the Stanford Systems Neuroscience and Pain Laboratory and a
Bioinformatics Engineer at Institut Curie in Paris, where I developed image analysis algorithms and
machine learning pipelines for cancer research.
</p>
</div>
<div class="credentials">
<h3>Education & Training</h3>
<ul>
<li>
<strong>PhD, Biomedical Engineering</strong><br>
Oregon Health & Science University, 2023–Present<br>
<em>Thesis:</em> Mathematical and computational modeling for precision oncology using simulation and deep learning (working title)<br>
<em>Advisors:</em> Dr. Young Hwan Chang & Dr. Laura Heiser
</li>
<li>
<strong>MD</strong><br>
Oregon Health & Science University (NIH-funded MSTP), 2021–Present
</li>
<li>
<strong>MS, Biomedical Informatics</strong><br>
Stanford University School of Medicine, 2016–2018
</li>
<li>
<strong>BS, Biomedical Computation</strong><br>
Stanford University School of Engineering, 2013–2017
</li>
</ul>
</div>
</div>
</section>
<section id="research">
<h2>Research</h2>
<div class="projects-grid">
<div class="project-card">
<h3>Agent-Based Modeling of the Tumor Microenvironment</h3>
<div class="project-tags">
<span class="tag">Agent-Based Models</span>
<span class="tag">Cancer Systems Biology</span>
<span class="tag">Precision Oncology</span>
</div>
<p>
Developing in silico agent-based models to map and control cancer progression in triple negative
breast cancer (TNBC). By simulating tumor-immune interactions and therapeutic interventions, this
work aims to identify actionable strategies for steering the tumor microenvironment toward
favorable states.
</p>
</div>
<div class="project-card">
<h3>Computational Analysis of Multiplexed Tissue Imaging</h3>
<div class="project-tags">
<span class="tag">Spatial Proteomics</span>
<span class="tag">Deep Learning</span>
<span class="tag">Single-Cell Analysis</span>
</div>
<p>
Building computational methods for high-plex immunofluorescence tissue images, including
COEXIST (serial multiplexed image integration), UniFORM (immunofluorescence normalization),
and SHIFT (histological-to-immunofluorescence translation). These tools enable robust
spatial analysis of cancer tissue at single-cell resolution.
</p>
</div>
<div class="project-card">
<h3>Temporal Analysis of 3D Cell Culture Systems</h3>
<div class="project-tags">
<span class="tag">Time-Course Imaging</span>
<span class="tag">Quality Control</span>
<span class="tag">Organoids</span>
</div>
<p>
Developing algorithms for temporal reassignment and correspondence evaluation in time-course
imaging of 3D cell cultures, enabling robust longitudinal tracking with integrated quality
control. This work supports drug response studies using patient-derived organoid models.
</p>
</div>
</div>
</section>
<section id="publications">
<h2>Selected Publications</h2>
<div class="publication">
<h3>Human interpretable grammar encodes multicellular systems biology models to democratize virtual cell laboratories</h3>
<p class="authors">Johnson JAI, Bergman DR, Rocha HL, Zhou DL, <strong>Cramer E</strong>, Mclean IC, et al.</p>
<p class="journal"><em>Cell</em>, 2025. <a href="https://doi.org/10.1016/j.cell.2025.06.048" target="_blank">doi:10.1016/j.cell.2025.06.048</a></p>
</div>
<div class="publication">
<h3>Temporal reassignment and correspondence evaluation with quality control for time-course imaging of 3D cell culture</h3>
<p class="authors"><strong>Cramer EM</strong>, Lopez-Vidal T, Johnson J, Wang V, Bergman DR, Weeraratna A, Burkhart R, Fertig EJ, Zimmerman JW, Heiser LM, Chang YH.</p>
<p class="journal"><em>Cell Reports Methods</em>, 2025;5(12):101237. <a href="https://doi.org/10.1016/j.crmeth.2025.101237" target="_blank">doi:10.1016/j.crmeth.2025.101237</a></p>
</div>
<div class="publication">
<h3>COEXIST: Coordinated single-cell integration of serial multiplexed tissue images</h3>
<p class="authors">Heussner RT, Watson CF, Eddy CZ, Wang K, <strong>Cramer EM</strong>, Creason AL, Mills GB, Chang YH.</p>
<p class="journal"><em>PLOS Computational Biology</em>, 2025. <a href="https://doi.org/10.1371/journal.pcbi.1013325" target="_blank">doi:10.1371/journal.pcbi.1013325</a></p>
</div>
<div class="publication">
<h3>UniFORM: Towards Universal Immunofluorescence Normalization for Multiplex Tissue Imaging</h3>
<p class="authors">Wang K, Ait-Ahmad K, Kupp S, Sims Z, <strong>Cramer EM</strong>, Sayar Z, Yu J, Wong MH, Mills GB, Eksi SE, Chang YH.</p>
<p class="journal"><em>Cell Reports Methods</em>, 2024. <a href="https://doi.org/10.1016/j.crmeth.2025.101172" target="_blank">doi:10.1016/j.crmeth.2025.101172</a></p>
</div>
<div class="publication">
<h3>CHOIRBM: An R package for exploratory data analysis and interactive visualization of pain patient body map data</h3>
<p class="authors"><strong>Cramer EM</strong>, Ziadni M, Scherrer KH, Mackey S, Kao MC.</p>
<p class="journal"><em>PLOS Computational Biology</em>, 2022. <a href="https://doi.org/10.1371/journal.pcbi.1010496" target="_blank">doi:10.1371/journal.pcbi.1010496</a></p>
</div>
<div class="publication">
<h3>Classifying chronic pain using multidimensional pain-agnostic symptom assessments and clustering analysis</h3>
<p class="authors">Gilam G, <strong>Cramer EM</strong>, Webber KA, Ziadni MS, Kao MC, Mackey SC.</p>
<p class="journal"><em>Science Advances</em>, 2021. <a href="https://doi.org/10.1126/sciadv.abj0320" target="_blank">doi:10.1126/sciadv.abj0320</a></p>
</div>
<div class="publication">
<h3>Acute pain predictors of postoperative pain resolution, opioid cessation, and recovery: Secondary analysis of the START randomized clinical trial</h3>
<p class="authors">Hah J, <strong>Cramer EM</strong>, Carroll I, Mackey S.</p>
<p class="journal"><em>JAMA Network Open</em>, 2019. <a href="https://doi.org/10.1001/jamanetworkopen.2019.0168" target="_blank">doi:10.1001/jamanetworkopen.2019.0168</a></p>
</div>
<div class="publication">
<h3>Predicting the incidence of pressure ulcers in the ICU using machine learning</h3>
<p class="authors"><strong>Cramer EM</strong>, Seneviratne M, Sharifi H, Ozturk A, Boussard T.</p>
<p class="journal"><em>eGEMs</em>, 2019. <a href="https://doi.org/10.5334/egems.307" target="_blank">doi:10.5334/egems.307</a></p>
</div>
<div class="pub-more">
<a href="https://www.ncbi.nlm.nih.gov/myncbi/eric.cramer.1/bibliography/public/" target="_blank">View complete list of publications →</a>
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<h3>Get in Touch</h3>
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<a href="https://www.linkedin.com/in/ericmcramer" target="_blank">LinkedIn</a>
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