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index.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1">
<meta name="author" content="Trimatrix Lab">
<meta name="description" content="">
<meta name="keywords" content="">
<title>Eric Bridgeford</title>
<link rel="icon" href="images/site/me.png">
<!--APPLE TOUCH ICON-->
<link rel="apple-touch-icon" href="images/site/apple-touch-icon.png">
<!-- GOOGLE FONT -->
<link href='https://fonts.googleapis.com/css?family=Raleway:500' rel='stylesheet' type='text/css'>
<link href='https://fonts.googleapis.com/css?family=Muli' rel='stylesheet' type='text/css'>
<!-- MATERIAL ICON FONT -->
<link href="https://fonts.googleapis.com/icon?family=Material+Icons" rel="stylesheet">
<!-- FONT AWESOME -->
<link rel="stylesheet" href="https://use.fontawesome.com/releases/v5.0.13/css/all.css" integrity="sha384-DNOHZ68U8hZfKXOrtjWvjxusGo9WQnrNx2sqG0tfsghAvtVlRW3tvkXWZh58N9jp" crossorigin="anonymous">
<!-- ANIMATION -->
<link href="stylesheets/vendors/animate.min.css" rel="stylesheet">
<!-- MAGNIFICENT POPUP -->
<link href="stylesheets/vendors/magnific-popup.css" rel="stylesheet">
<!-- SWIPER -->
<link href="stylesheets/vendors/swiper.min.css" rel="stylesheet">
<!-- MATERIALIZE -->
<link href="stylesheets/vendors/materialize.css" rel="stylesheet">
<!-- BOOTSTRAP -->
<link href="stylesheets/vendors/bootstrap.min.css" rel="stylesheet">
<!-- CUSTOM STYLE -->
<link href="stylesheets/style.css" id="switch_style" rel="stylesheet">
<link href="stylesheets/style_blue.css" rel="stylesheet">
<link rel="stylesheet" href="stylesheets/academicons.min.css"/>
<!--==========================================
SCRIPTS
===========================================-->
<script src="javascript/vendors/jquery-2.1.3.min.js"></script>
<script src="javascript/vendors/bootstrap.min.js"></script>
<script src="javascript/vendors/materialize.min.js"></script>
<script src="https://maps.googleapis.com/maps/api/js?key=AIzaSyAQ9929JwNFQWiL071hO2F9_DcHfa9Wvcc"></script>
<script src="javascript/vendors/markerwithlabel.min.js"></script>
<script src="javascript/vendors/retina.min.js"></script>
<script src="javascript/vendors/scrollreveal.min.js"></script>
<script src="javascript/vendors/swiper.jquery.min.js"></script>
<script src="javascript/vendors/jquery.magnific-popup.min.js"></script>
<script src="javascript/custom.js"></script>
</head>
<body>
<!--==========================================
PRE-LOADER
===========================================-->
<div id="loading">
<div id="loading-center">
<div id="loading-center-absolute">
<div class="box-holder animated bounceInDown">
<span class="load-box"><span class="box-inner"></span></span>
</div>
<!-- NAME & STATUS -->
<div class="text-holder text-center">
<h2>Eric Bridgeford</h2>
<h6>Postdoctoral Scholar & Statistician</h6>
</div>
</div>
</div>
</div>
<!--==========================================
HEADER
===========================================-->
<header id="home">
<nav id="theMenu" class="menu">
<!--MENU-->
<div id="menu-options" class="menu-wrap">
<!--PERSONAL LOGO-->
<div class="logo-flat">
<img alt="personal-logo" class="img-responsive" src="images/profile/eric.jpg">
</div>
<br>
<!--OPTIONS-->
<a href="#home"><i class="title-icon fa fa-user"></i>Home</a>
<a href="#about"><i class="title-icon fas fa-columns"></i>About</a>
<a href="#education"><i class="title-icon fa fa-graduation-cap"></i>Education</a>
<a href="#skills"><i class="title-icon fas fa-sliders-h"></i>Selected Skills</a>
<a href="#experience"><i class="title-icon fa fa-suitcase"></i>Experience</a>
<a href="#projects"><i class="title-icon fa fa-archive"></i>Projects</a>
<a href="#interest"><i class="title-icon fa fa-heart"></i>Interest</a>
<!--<a href="#testimonials"><i class="title-icon fa fa-users"></i>Testimonials</a> -->
<!--<a href="#pricing-table"><i class="title-icon fa fa-money"></i>Pricing</a> -->
<!--<a href="#blog"><i class="title-icon fa fa-pencil-square"></i>Blog</a>
<a href="#contact"><i class="title-icon fa fa-envelope"></i>Contact</a>-->
</div>
<!-- MENU BUTTON -->
<div id="menuToggle">
<div class="toggle-normal">
<i class="material-icons top-bar">remove</i>
<i class="material-icons middle-bar">remove</i>
<i class="material-icons bottom-bar">remove</i>
</div>
</div>
</nav>
<!--HEADER BACKGROUND-->
<div class="header-background section"></div>
</header>
<!--==========================================
V-CARD
===========================================-->
<div id="v-card-holder" class="section">
<div class="container">
<div class="row">
<div class="col-md-12 col-sm-12 col-xs-12">
<!-- V-CARD -->
<div id="v-card" class="card">
<!-- PROFILE PICTURE -->
<div id="profile" class="right">
<img alt="profile-image" class="img-responsive" src="images/profile/eric.jpg">
<div class="slant"></div>
<!--VIDEO PLAY BUTTON-->
<!--<div id="button-holder" class="btn-holder">
<div id="play-btn" class="btn-floating btn-large btn-play">
<i id="icon-play" class="material-icons">play_arrow</i>
</div>
</div>-->
</div>
<!--VIDEO CLOSE BUTTON-->
<!--<div id="close-btn" class="btn-floating icon-close">
<i class="fa fa-close"></i>
</div>-->
<div class="card-content">
<!-- NAME & STATUS -->
<div class="info-headings">
<h4 class="text-uppercase left">Eric Bridgeford</h4>
<h6 class="text-capitalize left">Postdoctoral Scholar & Statistician</h6>
</div>
<!--LINKS-->
<div class="links">
<!-- Github-->
<a href="https://github.com/ebridge2" id="first_one"
class="social btn-floating black"><i
class="fab fa-github"></i></a>
<!-- Linkedin-->
<a href="https://linkedin.com/in/ericbridgeford" class="social btn-floating blue darken-3"><i
class="fab fa-linkedin-in"></i></a>
<!-- GOOGLE Scholar-->
<a href="https://scholar.google.com/citations?user=ahNqfmAAAAAJ&hl=en" class="social btn-floating red"><i
class="ai ai-google-scholar-square ai-3x"></i></a>
<a href="https://www.researchgate.net/profile/Eric_Bridgeford" class="social btn-floating teal lighten-2"><i
class="ai ai-researchgate ai-3x"></i></a>
</div>
</div>
<!--HTML 5 VIDEO-->
<!-- <video id="html-video" class="video" poster="images/poster/poster.jpg" controls>
<source src="videos/........" type="video/webm">
<source src="videos/..........." type="video/mp4">
</video>-->
</div>
</div>
</div>
</div>
</div>
<!--==========================================
ABOUT
===========================================-->
<div id="about" class="section">
<div class="container">
<div class="row">
<div class="col-md-12">
<!-- DETAILS -->
<div id="about-card" class="card">
<div class="card-content">
<!-- ABOUT PARAGRAPH -->
<p>
Hello! I'm Eric Bridgeford. I am a postdoctoral scholar at Stanford University working towards developing statistical methods for neuroscience research. I am interested in end-to-end decision making in biological datasets, summarized in part by the below figure:
</p>
<center>
<img width="800 px" src="./images/profile/my_stuff.png">
</center>
<p>In many fields such as neuroimaging with expansive datasets, translating insights into clinical practice has proven problematic at best. I believe that disparities that arise across data collection sites in the form of batch effects, difficulties tuning analyses to properly adjust for potential confounding biases, difficulties identifying best practices for the construction of data derivatives (data pre-processing), and difficulties understanding how insights will translate when other pre-processing steps are taken, may be a potential source of this problem.</p>
</div>
<!-- BUTTONS -->
<div id="about-btn" class="card-action">
<div class="about-btn">
<!-- DOWNLOAD CV BUTTON -->
<a href="https://github.com/ebridge2/cv/raw/master/eric_cv.pdf" class="btn waves-effect">Download CV</a>
<!-- CONTACT BUTTON -->
<a href="#contact" class="btn waves-effect">Contact Me</a>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
<!--==========================================
EDUCATION
===========================================-->
<section id="education" class="section">
<div class="container">
<!-- SECTION TITLE -->
<div class="section-title">
<h4 class="text-uppercase text-center"><img src="images/icons/book.png" alt="demo">Education</h4>
</div>
<div id="timeline-education">
<!-- THIRD TIMELINE -->
<div class="timeline-block">
<!-- DOT -->
<div class="timeline-dot"><i class="fa fa-flask"></i></div>
<!-- TIMELINE CONTENT -->
<div class="card timeline-content">
<div class="card-content">
<!-- TIMELINE TITLE -->
<h6 class="timeline-title">Johns Hopkins University</h6>
<!-- TIMELINE TITLE INFO -->
<div class="timeline-info">
<h6>
<small>B.S. in Biomedical Engineering and Computer Science</small>
</h6>
<h6>
<small>September 2013 - May 2017</small>
</h6>
</div>
<!-- TIMELINE PARAGRAPH -->
<p>
I completed my undergraduate education at Johns Hopkins University, with my coursework focusing particularly at the intersection of statistics, bioengineering, and scalable computing.
</p>
<!-- BUTTON TRIGGER MODAL -->
<a href="#" class="modal-dot" data-toggle="modal" data-target="#modal-ujhu">
<i class="fa fa-ellipsis-h" aria-hidden="true"></i>
</a>
</div>
</div>
</div>
<!-- FOURTH TIMELINE -->
<div class="timeline-block">
<!-- DOT -->
<div class="timeline-dot"><i class="fa fa-graduation-cap"></i></div>
<!-- TIMELINE CONTENT -->
<div class="card timeline-content">
<div class="card-content">
<!-- TIMELINE TITLE -->
<h6 class="timeline-title">Johns Hopkins Department of Biostatistics</h6>
<!-- TIMELINE TITLE INFO -->
<div class="timeline-info">
<h6>
<small>Ph.D. in Biostatistics</small>
</h6>
<h6>
<small>September 2018 - August 2023</small>
</h6>
</div>
<!-- TIMELINE PARAGRAPH -->
<p>
I completed my graduate education at Johns Hopkins University in the Department of Biostatistics. I was be supervised by Dr. Brian Caffo and Dr. Joshua Vogelstein. My work focused on statistical methods for understanding measurement error in connectomes.
</p>
<!-- BUTTON TRIGGER MODAL -->
<a href="#" class="modal-dot" data-toggle="modal" data-target="#modal-gjhu">
<i class="fa fa-ellipsis-h" aria-hidden="true"></i>
</a>
</div>
</div>
</div>
</div>
</div>
</section>
<!--==========================================
SKILLS
===========================================-->
<section id="skills" class="section">
<div class="container">
<!-- SECTION TITLE -->
<div class="section-title">
<h4 class="text-uppercase text-center"><img src="images/icons/mixer.png" alt="demo">Selected Skills</h4>
</div>
<div class="row">
<div class="col-md-12 col-sm-12 col-xs-12">
<div id="skills-card" class="card">
<div class="card-content">
<div class="row">
<div class="col-md-4 col-sm-4 col-xs-12">
<!-- FIRST SKILL SECTION -->
<div class="skills-title">
<h6 class="text-center">Statistical</h6>
</div>
<div class="skillbar" data-percent="90%">
<div class="skillbar-title"><span>Package Development</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">90%</div>
</div>
<!-- FIRST SKILL BAR -->
<div class="skillbar" data-percent="90%">
<div class="skillbar-title"><span>Graph Inference</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">90%</div>
</div>
<div class="skillbar" data-percent="80%">
<div class="skillbar-title"><span>Statistical Theory</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">80%</div>
</div>
<!-- FIRST SKILL BAR -->
<div class="skillbar" data-percent="75%">
<div class="skillbar-title"><span>Dimensionality Reduction</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">75%</div>
</div>
<div class="skillbar" data-percent="70%">
<div class="skillbar-title"><span>Timeseries</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">70%</div>
</div>
</div>
<div class="col-md-4 col-sm-4 col-xs-12">
<!-- SECOND SKILL SECTION -->
<div class="skills-title">
<h6 class="text-center">Programming</h6>
</div>
<!-- FIRST SKILL BAR -->
<div class="skillbar" data-percent="90%">
<div class="skillbar-title"><span>R/python</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">90%</div>
</div>
<!-- FIRST SKILL BAR -->
<div class="skillbar" data-percent="75%">
<div class="skillbar-title"><span>Object-Oriented Programming</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">75%</div>
</div>
<!-- FIRST SKILL BAR -->
<div class="skillbar" data-percent="60%">
<div class="skillbar-title"><span>Scalable Computing</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">70%</div>
</div>
<!-- FIRST SKILL BAR -->
<div class="skillbar" data-percent="60%">
<div class="skillbar-title"><span>Bash</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">60%</div>
</div>
<!-- FIRST SKILL BAR -->
<div class="skillbar" data-percent="60%">
<div class="skillbar-title"><span>C/C++</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">60%</div>
</div>
</div>
<div class="col-md-4 col-sm-4 col-xs-12">
<!-- THIRD SKILL SECTION -->
<div class="skills-title">
<h6 class="text-center">Leadership</h6>
</div>
<!-- FIRST SKILL BAR -->
<!-- SECOND SKILL BAR -->
<div class="skillbar" data-percent="90%">
<div class="skillbar-title"><span>Communication</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">90%</div>
</div>
<!-- THIRD SKILL BAR -->
<div class="skillbar" data-percent="80%">
<div class="skillbar-title"><span>Product Delivery</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">80%</div>
</div>
<!-- FOURTH SKILL BAR -->
<div class="skillbar" data-percent="80%">
<div class="skillbar-title"><span>Feedback</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">80%</div>
</div>
<div class="skillbar" data-percent="70%">
<div class="skillbar-title"><span>Flexibility</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">70%</div>
</div>
<div class="skillbar" data-percent="70%">
<div class="skillbar-title"><span>SCRUM</span></div>
<div class="skillbar-bar"></div>
<div class="skill-bar-percent">70%</div>
</div>
</div>
</div>
<p><font color="#ffffff">0%: Beginner, 50%: Proficient, 100%: Expert</font></p>
</div>
</div>
</div>
</div>
</div>
</section>
<!--==========================================
EXPERIENCE
===========================================-->
<section id="experience" class="section">
<div class="container">
<!-- SECTION TITLE -->
<div class="section-title">
<h4 class="text-uppercase text-center"><img src="images/icons/layers.png" alt="demo">Experience</h4>
</div>
<div id="timeline-experience">
<!-- FIRST TIMELINE -->
<div class="timeline-block">
<!-- DOT -->
<div class="timeline-dot"><i class="fa fa-calculator"></i></div>
<!-- TIMELINE CONTENT -->
<div class="card timeline-content">
<div class="card-content">
<!-- TIMELINE TITLE -->
<h6 class="timeline-title">Undergraduate Researcher</h6>
<!-- TIMELINE TITLE INFO -->
<div class="timeline-info">
<h6>
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With Dr. Bassett and Dr. Muldoon, I aided in the development of a novel network statistic, the Small World Propensity. Our statistic provides an extension of small worldness to weighted graphs, a common element of real-world networks, and robustness to changes in edge density.
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With the NeuroData Team, I worked with Dr. Vogelstein to develop statistics for quantifying reliability in multi-scan scientific data and a processing pipeline for functional MRI connectomics to extend our existing pipeline for diffusion connectomics.
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With Dr. Vogelstein, Dr. Caffo, and Dr. Priebe, I extended our MRI connectomics pipeline for hyperparallelizability on AWS architecture and developed theoretical methods/software packages for manifold embedding techniques, independence testing, and graph statistics.
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As the Vice President of Engineering, I was responsible for contributing technological vision, coauthoring technical documents and patents, and managing the software and data analytics teams. I also managed the delivery of internal technical projects. The company has since re-focused as <a href="trimwire.com">Trimwire</a> by Atana, LLC.
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With Dr. Vogelstein, Dr. Caffo, and Dr. Priebe, I extended our MRI connectomics pipeline for hyperparallelizability on AWS architecture and developed theoretical methods/software packages for manifold embedding techniques, independence testing, and graph statistics.
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At Johns Hopkins, I obtained a Bachelor of Science (B.S.) in Biomedical Engineering and Computer Science, and a minor in pure mathematics. I graduated with General University Honors, Departmental Honors in Biomedical Engineering and Computer Science, and Special Honors in Computer Science for acceptance of my thesis <i>The Functional NeuroData Graph Service: A Hyperparallelizable One-Click Pipeline for the Reliable Estimation of Functional Connectomes</i>.
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I focused my coursework at the intersection of statistics, bioengineering, and scalable computing. My coursework included High Dimensional Approximation and Probability Theory, Statistical Learning and Signal Processing, Machine Learning, Probability and Statistics, Algorithms, Discrete Mathematics, Automata and Computation Theory, Systems Bioengineering, Statistical Mechanics and Thermodynamics, Object Oriented Software Engineering, Data Structures, Development of Database Management Systems, and Control Theory.
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I obtained my Ph.D. at Johns Hopkins University from the Department of Biostatistics under Dr. Brian Caffo and Dr. Joshua Vogelstein.
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My work focused on understanding sources of variability that permeate to neuroimaging data, such as those due to batch effects and pre-processing decision making. My coursework focused on statistical theory and methods, probability theory, Bayesian methods, and causal inference.
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<h6>Submitted and Works in Progress</h6>
<ol>
<li>Jaewon Chung, <u><b>Eric W. Bridgeford</b></u>, Michael Powell, Derek Pisner, Ting Xu, Joshua T. Vogelstein. <a href="https://www.biorxiv.org/content/10.1101/2023.04.02.532875v3"><i>The Heritability of Human Connectomes: a Causal Modeling Analysis</i></a>.</li>
<li><u><b>Eric W. Bridgeford</b></u>, Jaewon Chung, Brian Gilbert, Sambit Panda, Ashwin DeSilva, Censheng Shen, Brian Caffo, Joshua T. Vogelstein. <a href="https://arxiv.org/abs/2307.13868">Learning sources of variability from high-dimensional observational studies</a>.</li>
<li>Zeyi Wang, <u><b>Eric W. Bridgeford</b></u>, Shangsi Wang, Joshua T. Vogelstein, and Brian Caffo. <a href="https://arxiv.org/abs/2005.11911"><i>Statistical Analysis of Data Repeatability Measures</i></a>.</li>
<li>Vivek Gopalakrishnan, Jaewon Chung, <u><b>Eric W. Bridgeford</b></u>, Benjamin D. Pedigo, Jess Arroyo, Lucy Upchurch, G. Allan Johnson, Nian Wang, Youngser Park, Carey E. Priebe, Joshua T. Vogelstein. <a href="https://arxiv.org/abs/2011.14990"><i>Discovery of Multi-Level Network Differences Across Populations of Heterogeneous Connectomes</i></a>.</li>
<li>Sambit Panda, Satish Palaniappan, Junhao Xiong, <u><b>Eric W. Bridgeford</b></u>, Ronak Mehta, Cencheng Shen, Joshua T. Vogelstein. <a href="https://arxiv.org/abs/1907.02088"><i>hyppo: A Multivariate Hypothesis Testing Python Package</i></a>.</li>
<li>Gregory Kiar<sup>†</sup>, <u><b>Eric W. Bridgeford</b></u><sup>†</sup>, WillGray Roncal<sup>†</sup>, Consortium Reliability Reproducibility (CoRR), Vikram Chandrashakar, Disa Mhembere, Sephira Ryman, Xi-Nian Zuo,Daniel S Marguiles, RCameron Craddock, Carey E Priebe, Rex Jung, Vince D Calhoun, Brian Caffo, Randal Burns, Michael P Milham, Joshua T Vogelstein. <a href="https://www.biorxiv.org/content/early/2018/04/24/188706"><i>A High-Throughput Pipeline Identifies Robust Connectomes But Troublesome Variability</i></a>.</li>
</ol>
<h6>Peer-Reviewed Journal Articles</h6>
<ol>
<li><u><b>Eric W. Bridgeford</b></u>, Michael Powell, Gregory Kiar, Stephanie Noble, Jaewon Chung, Sambit Panda, Ross Lawrence, Ting Xu, Michael Milham, Brian Caffo, Joshua T. Vogelstein. <a href="https://www.biorxiv.org/content/10.1101/2021.09.03.458920v7"><i>When no answer is better than a wrong answer: a causal perspective on batch effects</i></a>. <i>In press at Imaging Neuroscience</i>.</li>
<li>Benjamin D. Pedigo, Mike Powell, <u><b>Eric W. Bridgeford</b></u>, Michael Winding, Carey E. Priebe, Joshua T. Vogelstein. <i><a href="https://elifesciences.org/articles/83739">Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome</a></i>. Published in eLife (2023).</li>
<li>Ting Xu, Gregory Kiar, Jae Wook Cho, <u><b>Eric W. Bridgeford</b></u>, Aki Nikolaidis, Joshua T. Vogelstein, Michael P. Milham. <a href="https://www.nature.com/articles/s41592-023-01901-3"><i>ReX: an integrative tool for quantifying and optimizing measurement reliability for the study of individual differences</i></a>. Published in Nature Methods (2023).</li>
<li>Jaewon Chung, <u><b>Eric W. Bridgeford</b></u>, Jess Arroyo, Benjamin D. Pedigo, Ali Saad-Eldin, Vivek Gopalakrishnan, Liang Xiang, Carey E. Priebe, Joshua T. Vogelstein. <a href="https://www.annualreviews.org/doi/abs/10.1146/annurev-statistics-042720-023234"><i>Statistical Connectomics</i></a>. Published in Annual Review of Statistics and its Application (2021).</li>
<li><u><b>Eric W. Bridgeford</b></u>, Shangsi Wang, Zhi Yang, Zeyi Wang, Ting Xu, Cameron Craddock, Jayanta Dey, Gregory Kiar, William Gray-Roncal, Carlo Colantuoni, Christopher Douville, Stephanie Noble, Carey E. Priebe, Brian Caffo, Michael Milham, Xi-Nian Zuo, Consortium for Reliability and Reproducibility, and Joshua T. Vogelstein. <a href="https://www.biorxiv.org/content/10.1101/802629v8"><i>Eliminating accidental deviations to minimize generalization error and maximize replicability: applications in connectomics and genomics</i></a>. PLOS Computational Biology (2021).</li>
<li>Roger Peng, Athena Chen, <u><b>Eric W. Bridgeford</b></u>, Jeff Leek, and Stephanie Hicks. <a href="https://www.tandfonline.com/doi/full/10.1080/26939169.2021.1971586"><i>Diagnosing Data Analytic Problems in the Classroom</i></a>. In production in the Journal of Statistics and Data Science Education (2021).</li>
<li>Jaewon Chung, <u><b>Eric W. Bridgeford</b></u>, Jesus Arroyo, Benjamin D. Pedigo, Ali Saad-Eldin, Vivek Gopalakrishnan, Liang Xiang, Carey E. Priebe, and Joshua T. Vogelstein. <a href="https://www.annualreviews.org/doi/abs/10.1146/annurev-statistics-042720-023234"><i>Statistical Connectomics</i></a>. Published in the Annual Review of Statistics and Its Application (Volume 8, 2021).</li>
<li>Ross M. Lawrence, <u><b>Eric W. Bridgeford</b></u>, Patrick E. Myers, Ganesh C. Arvapalli, Sandhya C. Ramachandran, Derek A. Pisner, Paige F. Frank, Allison D. Lemmer, Aki Nikolaidis, and Joshua T. Vogelstein. <a href="https://www.nature.com/articles/s41597-021-00849-3"><i>Standardizing human brain parcellations</i></a>. Published in Nature, Scientific Data (March 2021).</li>
<li>Joshua T. Vogelstein<sup>†</sup>, <u><b>Eric W. Bridgeford</b></u><sup>†</sup>, Minh Tang, Da Zheng, Christopher Douville, Randal Burns, and Mauro Maggioni. <a href="https://www.nature.com/articles/s41467-021-23102-2"><i>Supervised dimensionality reduction for big data</i></a>. Published in Nature Communications (May, 2021).</li>
<li>Jordan Yoder, Li Chen, Henry Pao, <u><b>Eric W. Bridgeford</b></u>, Keith Levin, Donniell Fishkind, Carey E Priebe, Vince Lyzinski. <a href="https://par.nsf.gov/servlets/purl/10168174"><i>Vertex nomination: The canonical sampling and the extended spectral nomination schemes</i></a>. Published in Journal of Computational Statistics and Data Analysis (May, 2020).</li>
<li>Jaewon Chung, Benjamin D. Pedigo, <u><b>Eric W. Bridgeford</b></u>, Bijan Varjavand, Hayden Helm, and Joshua T. Vogelstein. <a href="http://jmlr.org/papers/volume20/19-490/19-490.pdf"><i>GraSPy: Graph Statistics in Python</i></a>. Published in Journal of Machine Learning Research (September 2019).</li>
<li>Joshua T. Vogelstein, <u><b>Eric W. Bridgeford</b></u>, Benjamin D. Pedigo, Jaewon Chung, Keith Levin, Brett Mensch, and Carey E. Priebe. <a href="https://www.biorxiv.org/node/681822.external-links.html"><i>Connectal Coding: Discovering the Structures Linking Cognitive Phenotypes to Individual Histories</i></a>. Current Opinions in Neurobiology (April 2019).</li>
<li>Cencheng Shen, <u><b>Eric W. Bridgeford</b></u>, Qing Wang, Carey E. Priebe, Mauro Maggioni, and Joshua T. Vogelstein. <a href="https://arxiv.org/abs/1609.05148"><i>Discovering Relationships and their Structures Across Disparate Data Modalities</i></a>. Published in Elife (February 2019).</li>
<li>Carey E. Priebe, Youngser Park, Joshua T. Vogelstein, John M. Conroy, Vince Lyzinski, Minh Tang, Avanti Athreya, Joshua Cape, and <u><b>Eric W. Bridgeford</b></u>. <a href="https://www.pnas.org/content/early/2019/03/07/1814462116"><i> On a ’Two Truths’ Phenomenon in Spectral Graph Clustering</i></a>. In press at Proceedings of the National Academy of Sciences (PNAS).</li>
<li>Joshua T. Vogelstein, Eric Perlman, Benjamin Falk, Alex Baden, William Gray Roncal, Vikram Chandrashekhar, Forrest Collman, Sharmishtaa Seshamani, Jesse L. Patsolic, Kunal Lillaney, Michael Kazhdan, Robert Hider, Derek Pryor, Jordan Matelsky, Timothy Gion, Priya Manavalan, Brock Wester, Mark Chevillet, Eric T. Trautman, Khaled Khairy, <u><b>Eric W. Bridgeford</b></u>, Dean M. Kleissas, Daniel J. Tward, Ailey K. Crow, Brian Hsueh, Matthew A. Wright, Michael I. Miller, Stephen J. Smith, R. Jacob Vogelstein, Karl Deisseroth, and Randal Burns. <a href="https://www.nature.com/articles/s41592-018-0181-1"><i>A community-developed open-source computational ecosystem for big neuro data</i></a>. Published in Nature Methods (Nov. 2018)</li>
<li>Sarah F. Muldoon, <u><b>Eric W. Bridgeford</b></u>, and Danielle S. Bassett. <a href="https://www.nature.com/articles/srep22057"><i>Small-World Propensity in Weighted, Real-World Networks</i></a>. Published in Nature, Scientific Reports (February 2016).</li>
</ol>
<h6>Peer-Reviewed Conference Proceedings</h6>
<ol>
<li>Qingyang Wang, Michael A. Powell, Ali Geisa, <u><b>Eric W. Bridgeford</b></u>, Carey E. Priebe, Joshua T. Vogelstein. <a href="https://ieeexplore.ieee.org/document/10377525"><i>Why do networks have inhibitory/negative connections?</i></a> In Proceedings of IEEE/CVF International Conference on Computer Vision (ICCV, 2023).</li>
<li>Qingyang Wang, Michael Alan Powell, <u><b>Eric W. Bridgeford</b></u>, Ali Geisa, Joshua T. Vogelstein. <a><i>Polarity Is All You Need to Learn and Transfer Faster</i></a>. International Conference of Machine Learning (ICML, 2023).</li>
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<sup>†</sup> These authors contributed equally to the work.
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<h6>Books</h6>
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<li><u><b>Eric W. Bridgeford</b></u>, Alexander Loftus, Joshua T. Vogelstein. <a href="https://www.overleaf.com/read/cdmbzwkrxtbv"><i>Hands on Network Machine Learning</i></a>. <i>Publishing contract with Cambridge University Press</i> (2024).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="https://ericwb.me/prob_book/coverpage.html"><i>Measure Theoretic Probability Theory</i></a>. <i>Work in progress</i>.</li>
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<h6>Book Chapters</h6>
<ol>
<li><u><b>Eric W. Bridgeford</b></u>, Daniel Sussman, Vince Lyzinski, Yichen Qin, Youngser Park, Brian Caffo, Carey Priebe, Joshua T. Vogelstein. <a href="https://www.sfn.org/-/media/SfN/Documents/NEW-SfN/Careers/2018/Career-Tools-and-Resources/Scientific-Short-Courses/20190418_2018_sc2_course_book_final.pdf">What Is Connectome Coding?</a>, In: Functional, Structural, and Molecular Imaging, and Big Data Analysis (edited by E. Boyden and K.Chung), pp. 63 - 74, <i>Society for Neuroscience</i> (2018).</li>
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<h6>R Packages</h6>
<ol>
<li><u><b>Eric W. Bridgeford</b></u>, Michael Powell, Brian Caffo, Joshua T. Vogelstein. <a href=""><i>causalBatch: Causal Batch Effects</i></a>. <i>CRAN Package</i> (2024).</li>
<li><u><b>Eric W. Bridgeford</b></u>, Censheng Shen, Shangsi Wang, and Joshua T. Vogelstein. <a href="https://github.com/neurodata/mgc"><i>Multiscale Graph Correlation</i></a>. <i>CRAN Package</i> (2019). DOI: <a href="https://doi.org/10.5281/zenodo.1246966">10.5281/zenodo.1246966</a>.</li>
<li><u><b>Eric W. Bridgeford</b></u>, Minh Tang, Jason Yim, and Joshua T. Vogelstein. <a href="https://github.com/neurodata/lol"><i>Linear Optimal Low-Rank Projection (LOL)</i></a>. <i>CRAN Package</i> (2018). DOI: <a href="https://doi.org/10.5281/zenodo.1246978">10.5281/zenodo.1246978</a>.</li>
<li><u><b>Eric W. Bridgeford</b></u>, Ronak Mheta, Coleman Zhang, and Joshua Vogelstein. <a href="https://github.com/neurodata/graphstats"><i>Graph Statistics</i></a>. Devtools-installable Package.</li>
<li><u><b>Eric W. Bridgeford</b></u> and Joshua T. Vogelstein. <a href="https://github.com/neurodata/slb"><i>Statistical Learning Benchmarks</i></a>. Devtools-installable Package.</li>
</ol>
<h6>Python Packages</h6>
<ol>
<li>Sambit Panda, Satish Palaniappan, Junhao Xiong, <u><b>Eric W. Bridgeford</b></u>, Ronak Mehta, Cencheng Shen, Joshua T. Vogelstein. <a href="https://github.com/neurodata/hyppo"><i>Hyppo</i></a>. <i>Pypi Package</i> (2018).</li>
<li>Jaewon Chung, Benjamin D. Pedigo, <u><b>Eric W. Bridgeford</b></u>, Bijan Varjavand, Hayden Helm, Joshua T. Vogelstein. <a href="https://pypi.org/project/graspy/0.0.0.1/"><i>GraSPy: Graph Statistics in Python</i></a>. <i>Pypi Package</i> (2018).</li>
<li>Gregory Kiar, William Gray Roncal, Disa Mhembere, <u><b>Eric W. Bridgeford</b></u>, Randal Burns, and Joshua T. Vogelstein. <a href="https://github.com/neurodata/ndmg">Neurodata MRI Graphs (ndmg)</a>. DOI: <a href="https://doi.org/10.5281/zenodo.595684">10.5281/zenodo.595684</a>.</li>
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<li>Gregory Kiar, William R Gray Roncal, Disa Mhembere, <u><b>Eric W. Bridgeford</b></u>, Shan gsi Wang, Carey Priebe, Randal Burns, and Joshua T Vogelstein. <a href="https://f1000research.com/posters/5-2568"><i>MR Graphs with Rich attribUTEs DataBase (Mr. GruteDB).</i></a>. Organization of Human Brain Mapping (June 2016).</li>
<li><u><b>Eric W. Bridgeford</b></u>, Gregory Kiar, Will Gray Roncal, Disa Mehembre, Randal Burns, Joshua T Vogelstein. <a href="http://dx.doi.org/10.6084/m9.figshare.1549708"><i>MRImages to Graphs: A One Click Community Pipeline for MR Connectome Analysis</i></a>. Institute for Computational Medicine Night (March 2016).</li>
<li>Gregory Kiar, et al. <a href="http://dx.doi.org/10.6084/m9.figshare.1549710"><i>Community Connectomics via Cloud Computing Utilizing m2g - a Reference Pipeline</i></a>. Organization for Human Brain Mapping (June 2015).</li>
<li>Sarah F. Muldoon, <u><b>Eric W. Bridgeford</b></u>, Danielle S. Bassett. <a href="https://figshare.com/account/articles/2062056"><i>Quantifying Small Worldness in Weighted Brain Networks: Small-World Propensity</i></a>. Society for Neuroscience (October 2015).</li>
<li>Joshua T. Vogelstein, et al. <i>The Open Connectome Project & Neurodata: Enabling Data Driven Neuroscience at Scale</i>. Society for Neuroscience (October 2015).</li>
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<h6>Courses</h6>
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<li><u><b>Eric W. Bridgeford</b></u> and Jaewon Chung. <a href="ericwb.me/lectures/intro_graph_ML.html#1"><i>Hands on Network Machine Learning</i></a>. Continuing Education Course at: <i>Joint Statistical Meetings</i> (JSM, 2023).</li>
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<h6>Invited Lectures</h6>
<ol>
<li><u><b>Eric W. Bridgeford</b></u> and Jaewon Chung. <a href="ericwb.me/lectures/intro_graph_ML.html#1"><i>Hands on Network Machine Learning</i></a>. Course module for: <i>Johns Hopkins University Applied Physics Laboratory (APL) Advanced Graph Analytics</i> (2023).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="https://docs.google.com/presentation/d/1Ufn0H_IZ_nE1qXN3Yh5KatBo1ptGn3SHpSdd7-htVnk/edit?usp=sharing"><i>Introduction to Network-Valued Data</i></a>. Guest Lecturer for: <i>Introduction to Computational Medicine Course at Johns Hopkins University</i> (2023).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="https://docs.google.com/presentation/d/1eDjufRWWXzhvnI76aD_UKc4w4uxg9ijjbQN6rE7sRpM/edit?usp=sharing"><i>Community Detection</i></a>. Guest Lecturer for: <i>Introduction to Computational Medicine Course at Johns Hopkins University</i> (2023).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="https://docs.google.com/presentation/d/1Ufn0H_IZ_nE1qXN3Yh5KatBo1ptGn3SHpSdd7-htVnk/edit?usp=sharing"><i>Introduction to Network-Valued Data</i></a>. Guest Lecturer for: <i>Introduction to Computational Medicine Course at Johns Hopkins University</i> (2022).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="https://docs.google.com/presentation/d/1eDjufRWWXzhvnI76aD_UKc4w4uxg9ijjbQN6rE7sRpM/edit?usp=sharing"><i>Community Detection</i></a>. Guest Lecturer for: <i>Introduction to Computational Medicine Course at Johns Hopkins University</i> (2022).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="https://www.youtube.com/watch?v=zewLyPPlqqg&ab_channel=ABCD-ReproNimCourse"><i>Unsupervised Machine Learning with Connectomics Data</i></a>. Course module for: <i>ABCD ReproNim Course</i> (2022).</li>
</ol>
<h6>Miscellaneous Talks</h6>
<ol>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="ericwb.me/lectures/nimh_113023.html#1"><i>GrasPy: Causal Analyses on Populations of Graphs</i></a>. PI meeting talk at: <i>National Institutes of Mental Health</i> (2023).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <i>Hands on Network Machine Learning</i>. Lightning round talk at: <i>Berlin Connectomics Meeting</i> (2022).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <a href="https://www.pathlms.com/ohbm/courses/8246/sections/12541/video_presentations/115958"><i>A Principled Approach to Statistical Connectomics and Mega-Analysis</i></a>. Oral Session at: <i>Organization of Human Brain Mapping</i> (OHBM, 2018).</li>
<li>Joshua T. Vogelstein and <u><b>Eric W. Bridgeford</b></u>. <a href="https://github.com/neurodatadesign/sfn17"><i>Quantifying Differences between Diffusion and Functional Connectomes</i></a>. <i>Society for Neuroscience</i> (2017).</li>
<li><u><b>Eric W. Bridgeford</b></u>. <i>From the Functional Brain to the Connectome: An Introduction to Neuroscience Research
in the 21st Century</i>. JHU Splash (2016).</li>
</ol>
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