Adam Saunders

I am a PhD student at Vanderbilt University researching brain MRI and AI.

Summary

An electrical engineering PhD student studying medical imaging research focused on applying artificial intelligence tools to impute missing information from imperfect data. Strengths in analytical skills and scientific communication.

Education

  • Vanderbilt University
    August 2023 - Present
    • PhD, Electrical and Computer Engineering
  • University of Dayton
    August 2019 - May 2023
    • Bachelor of Electrical Engineering, minor in Mathematics, summa cum laude

Experience

  • Research Assistant
    July 2023 - Present

    Vanderbilt University
    • Performed medical imaging research in the Medical-image Analysis and Statistical Interpretation Lab and Vanderbilt Lab for Immersive AI Translation
    • Collaborated with scientists and clinicians to communicate published scientific findings
  • Undergraduate Music Minister
    August 2019 - June 2023

    University of Dayton
    • Planned and composed weekly hymns for campus Masses
    • Led vocalists and instrumentalists by accompanying on piano
  • SULI Intern
    June 2022 - August 2022

    Oak Ridge National Laboratory
    • Explored deep learning algorithms on an internationally-ranked supercomputer
    • Performed and presented medical image processing research
  • Physics Teaching Assistant
    January 2021 - May 2021
    January 2022 - May 2022

    University of Dayton
    • Empowered over 50 students to learn calculus-based mechanics
    • Assisted in the development of testing materials and led weekly office hours
  • Computer Engineering Intern
    May 2021 - August 2021

    Defense Research Associates, Inc.
    • Designed and implemented digital hardware interfaces for sensors
    • Presented technical results and documentation for future deployment
  • Physics Grader
    January 2020 - May 2020

    University of Dayton
    • Evaluated exams and group work for over 50 students
    • Led weekly homework help sessions in a challenging, fast-paced class

Journal Publications

  • Lucas W. Remedios, Chloe Cho, Trent M. Schwartz, Dingjie Su, Gaurav Rudravaram, Chenyu Gao, Aravind R. Krishnan, Adam M. Saunders, Michael E. Kim, Shunxing Bao, Thomas A. Lasko, Alvin C. Powers, Bennett A. Landman, and John Virostko. “Lifespan Pancreas Morphology for Control vs Type 2 Diabetes using AI on Largescale Clinical Imaging”. Clinical Anatomy, 2026. doi: 10.1002/ca.70077

  • Michael E. Kim, Gaurav Rudravaram, Adam M. Saunders, Chenyu Gao, Karthik Ramadass, Nancy R. Newlin, Praitayini Kanakaraj, Sam Bogdanov, Angela L. Jefferson, Victoria L. Morgan, Alexandra Roche, Dario J. Englot, Susan M. Resnick, Lori L. Beason Held, Murat Bilgel, Laurie E. Cutting, Laura A. Barquero, Micah A. D’Archangel, Tin Q. Nguyen, Kathryn L. Humphreys, Yanbin Niu, Sophia Vinci-Booher, Carissa J. Cascio, Kimberly R. Pechman, Niranjana Shashikumar, The HABS-HD Study Team, Alzheimer’s Disease Neuroimaging Initiative, The BIOCARD Study Team, Zhiyuan Li, Panpan Zhang, John C. Gore, Yihao Liu, Lianrui Zuo, Yuankai Huo, Derek B. Archer, Timothy J. Hohman, L. Taylor Davis, Kurt G. Schilling, Daniel C. Moyer, and Bennett A. Landman. “Charting Confidence in White Matter Brain Charts: Enabling Study Planning Through Stability Validation”. Journal of Medical Imaging, 2026. doi: 10.1117/1.JMI.13.5.054001

  • Elyssa M. McMaster, Nancy R. Newlin, Chloe Cho, Gaurav Rudravaram, Adam M. Saunders, Aravind R. Krishnan, Lucas W. Remedios, Michael E. Kim, Hanliang Xu, Kurt G. Schilling, François Rheault, Laurie E. Cutting, and Bennett A. Landman. “Contrastive learning and advanced bundle metrics outperform fractional anisotropy for Alzheimer’s disease diffusion MRI prediction Findings from the Beyond FA challenge”. Journal of Medical Imaging, 2026. doi: 10.1117/1.JMI.13.5.054003

  • Aravind R. Krishnan, Thomas Z. Li, Lucas W. Remedios, Michael E. Kim, Chenyu Gao, Gaurav Rudravaram, Elyssa M. McMaster, Adam M. Saunders, Shunxing Bao, Kaiwen Xu, Lianrui Zuo, Kim L. Sandler, Fabien Maldonado, Yuankai Huo, and Bennett A. Landman. “Multipath CycleGAN for harmonization of paired and unpaired low-dose lung computed tomography reconstruction kernels”. Medical Physics, 2025. doi: 10.1002/mp.70120

  • Elyssa M. McMaster, Nancy R. Newlin, Chloe Cho, Gaurav Rudravaram, Adam M. Saunders, Aravind R. Krishnan, Lucas W. Remedios, Michael E. Kim, Hanliang Xu, Kurt G. Schilling, François Rheault, Laurie E. Cutting, and Bennett A. Landman. “Sensitivity of quantitative diffusion MRI tractography and microstructure to anisotropic spatial sampling”. Magnetic Resonance in Medicine, 2025. doi: 10.1016/j.mri.2025.110539

  • Elyssa M. McMaster, Nancy R. Newlin, Gaurav Rudravaram, Adam M. Saunders, Aravind R. Krishnan, Lucas W. Remedios, Michael E. Kim, Hanliang Xu, Derek B. Archer, Kurt G. Schilling, François Rheault, Laurie E. Cutting, and Bennett A. Landman. “Harmonized connectome resampling for variance in voxel sizes”. Magnetic Resonance Imaging, 2025. doi: 10.1016/j.mri.2025.110424

  • Chenyu Gao, Michael E. Kim, Karthik Ramadass, Praitayini Kanakaraj, Aravind R. Krishnan, Adam M. Saunders, Nancy R. Newlin, Ho Hin Lee, Qi Yang, Warren D. Taylor, Brian D. Boyd, Lori L. Beason-Held, Susan M. Resnick, Lisa L. Barnes, David A. Bennett, Katherine D. Van Schaik, Derek B. Archer, Timothy J. Hohman, Angela L. Jefferson, Ivana Işgum, Daniel Moyer, Yuankai Huo, Kurt G. Schilling, Lianrui Zuo, Shunxing Bao, Nazirah Mohd Khairi, Zhiyuan Li, Christos Davatzikos, and Bennett A. Landman for the Alzheimer’s Disease Neuroimaging Initiative and the BIOCARD Study team. “Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease”. Imaging Neuroscience, 2025. doi: 10.1162/imag_a_00552

  • Adam M. Saunders, Michael E. Kim, Chenyu Gao, Lucas W. Remedios, Aravind R. Krishnan, Kurt G. Schilling, Kristin P. O’Grady, Seth A. Smith, and Bennett A. Landman. “Comparison and calibration of MP2RAGE quantitative T1 values to multi-TI inversion recovery T1 values”. Magnetic Resonance Imaging, 2025. doi: 10.1016/j.mri.2025.110322

  • Lucas W. Remedios, Han Liu, Samuel W. Remedios, Lianrui Zuo, Adam M. Saunders, Shunxing Bao, Yuankai Huo, Alvin C. Powers, John Virostko, and Bennett A. Landman. “Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI”. Journal of Medical Imaging, 2025. doi: 10.1117/1.JMI.12.2.024008

  • Lucas W. Remedios, Chloe Cho, Trent M. Schwartz, Dingjie Su, Gaurav Rudravaram, Chenyu Gao, Aravind R. Krishnan, Adam M. Saunders, Michael E. Kim, Shunxing Bao, Alvin C. Powers, Bennett A. Landman, and John Virostko. “Data-driven abdominal phenotypes of type 2 diabetes in lean, overweight, and obese cohorts”. Journal of Medical Imaging, 2025. doi: 10.1117/1.JMI.12.6.064006

  • Ho Hin Lee*, Adam M. Saunders*, Michael E. Kim, Samuel W. Remedios, Lucas W. Remedios, Yucheng Tang, Qi Yang, Xin Yu, Shunxing Bao, Chloe Cho, Louise A. Mawn, Tonia S. Rex, Kevin L. Schey, Blake E. Dewey, Jeffrey M. Spraggins, Jerry L. Prince, Yuankai Huo, and Bennett A. Landman. “Super-resolution multi-contrast unbiased eye atlases with deep probabilistic refinement”. Journal of Medical Imaging, 2024. doi: 10.1117/1.JMI.11.6.064004 *Equal contribution.

  • Lucas W. Remedios, Shunxing Bao, Samuel W. Remedios, Ho Hin Lee, Leon Y. Cai, Thomas Li, Ruining Deng, Nancy R. Newlin, Adam M. Saunders, Can Cui, Jia Li, Qi Liu, Ken S. Lau, Joseph T. Roland, Mary K. Washington, Lori A. Coburn, Keith T. Wilson, Yuankai Huo, and Bennett A. Landman. “Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology”. Journal of Medical Imaging, 2024. doi: 10.1117/1.JMI.11.6.067501

  • Elyssa M. McMaster, Gaurav Rudravaram, Michael E. Kim, Trent M. Schwartz, Chloe Scholten, Jongyeon Yoon, Adam M. Saunders, Andre T.S. Hucke, Karthik Ramadass, Emily M. Harriott, Steven L. Meisler, Simon N. Vandekar, Allen Newton, Seth A. Smith, Saikat Sengupta, Kathryn L. Humphreys, Sarah Osmundson, Daniel C. Moyer, Laurie E. Cutting, and Bennett A. Landman. “Bundle-level effects of diffusion MRI harmonization in the HBCD study”. Submitted to IEEE Transactions on Biomedical Engineering.

  • Adam M. Saunders, Gaurav Rudravaram, Michael E. Kim, Elyssa M. McMaster, Yifan Shuai, Warren Boschen, Sophie Lin, Suzana Herculano-Houzel, Daniel C. Colvin, Yurui Gao, Kurt G. Schilling, Adam W. Anderson, and Bennett A. Landman. “Separating mixtures of single-fiber orientation distributions for increased sensitivity to crossing white matter fibers”. Submitted to Human Brain Mapping.

  • Michael E. Kim, Chenyu Gao, Karthik Ramadass, Gaurav Rudravaram, Elyssa M. McMaster, Adam M. Saunders, Yisu Yang, Elias Levy, Praitayini Kanakaraj, Nancy R. Newlin, Zhiyuan Li, Nazirah Mohd Khairi, Blake E. Dewey, The HABS-HD Study Team, Alzheimer’s Disease Neuroimaging Initiative, Kurt G. Schilling, Derek B. Archer, Timothy J. Hohman, Bennett A. Landman, and Yihao Liu. “Large-Scale Deployment and Analytical Implications of Structured Quality Control in Diffusion Magnetic Resonance Imaging”. Submitted to SPIE Journal of Medical Imaging.

Conference Papers

  • Elyssa M. McMaster, Gaurav Rudravaram, Michael E. Kim, Trent M. Schwartz, Chloe Scholten, Adam M. Saunders, Andre T. S. Hucke, Karthik Ramadass, Emily M. Harriott, Steven L. Meisler, Simon N. Vandekar, Allen Newton, Seth A. Smith, Saikat Sengupta, Kathryn L. Humphreys, Sarah Osmundson, Daniel Moyer, Laurie E. Cutting, and Bennett A. Landman. “Harmonization mitigates diffusion MRI scanner effects in infancy: insights from the HEALthy Brains and Child Development (HBCD) Study”. Accepted to IEEE International Symposium on Biomedical Imaging, April 2026. doi: 10.48550/arXiv.2604.00246

  • Chloe Scholten*, Elyssa M. McMaster*, Adam M. Saunders, Michael E. Kim, Gaurav Rudravaram, Elias Levy, Bryce Geeraert, Lianrui Zuo, Simon Vandekar, Catherine Lebel, and Bennett A. Landman. “Evaluation of neuroCombat and deep learning harmonization for multi-site MR neuroimaging in a pediatric population with prenatal alcohol exposure”. Accepted to IEEE International Symposium on Biomedical Imaging, April 2026. doi: 10.48550/arXiv.2604.00251 *Equal contribution.

  • Adam M. Saunders, Lucas W. Remedios, Elyssa M. McMaster, Jongyeon Yoon, Gaurav Rudravaram, Adam Sadriddinov, Praitayini Kanakaraj, Bennett A. Landman, and Adam W. Anderson. “DeepFixel: Crossing white matter fiber identification through spherical convolutional neural networks”. SPIE Medical Imaging: Clinical and Biomedical Imaging, February 2026. doi: 10.1117/12.3085833

  • Adam M. Saunders, Michael E. Kim, Gaurav Rudravaram, Lucas W. Remedios, Chloe Cho, Elyssa M. McMaster, Daniel R. Gillis, Yihao Liu, Lianrui Zuo, Bennett A. Landman, and Tonia S. Rex. “Phenotype discovery of traumatic brain injury segmentations from heterogeneous multi-site data”. SPIE Medical Imaging: Image Processing, February 2026. doi: 10.1117/12.3085847

  • Michael E. Kim, Gaurav Rudravaram, Adam M. Saunders, Chenyu Gao, Karthik Ramadass, Nancy R. Newlin, Praitayini Kanakaraj, Sam Bogdanov, Derek Archer, Timothy J. Hohman, Angela L. Jefferson, Victoria L. Morgan, Alexandra Roche, Dario J. Englot, Susan M. Resnick, Lori L. Beason Held, Murat Bilgel, Laurie E. Cutting, Laura A. Barquero, Micah A. D’Archangel, Tin Q. Nguyen, Kathryn L. Humphreys, Yanbin Niu, Sophia Vinci-Booher, Carissa J. Cascio, Kimberly R. Pechman, Niranjana Shashikumar, The HABS-HD Study Team, Alzheimer’s Disease Neuroimaging Initiative, The BIOCARD Study Team, Zhiyuan Li, Simon N. Vandekar, Panpan Zhang, John C. Gore, Yihao Liu, Lianrui Zuo, Kurt G. Schilling, Daniel C. Moyer, and Bennett A. Landman. “Analytic Bounds on GAMLSS Model Variability of Normative White Matter Brain Charts”. SPIE Medical Imaging: Image Processing, February 2026. doi: 10.1117/12.3085643

  • Chloe Cho, Andrew J. McNeil, Bohan Jiang, Adam M. Saunders, Gaurav Rudravaram, Yihao Liu, Daniel Moyer, Benoit M. Dawant, Bennett A. Landman, and Eric R. Tkaczyk. “DermIDS: Dermatology imaging data structure for scalable and interoperable AI systems”. SPIE Medical Imaging: Imaging Informatics, February 2026. doi: 10.1117/12.3085989

  • Elyssa M. McMaster, Michael E. Kim, Nancy R. Newlin, Gaurav Rudravaram, Adam M. Saunders, Aravind R. Krishnan, Jongyeon Yoon, Ji S. Kim, Bryce L. Geeraert, Meaghan V. Perdue, Catherine Lebel, Daniel Moyer, Kurt G. Schilling, Laurie E. Cutting, and Bennett A. Landman. “Personalized white matter bundle segmentation for early childhood”. SPIE Medical Imaging: Image Processing, February 2026. doi: 10.1117/12.3086478

  • Gaurav Rudravaram, Lianrui Zuo, Michael E. Kim, Adam M. Saunders, Praitayini Kanakaraj, Nancy R. Newlin, Aravind R. Krishnan, Elyssa M. McMaster, Chloe Cho, Susan M. Resnick, Lori L. Beason Held, Derek Archer, Timothy J. Hohman, Daniel C. Moyer, and Bennett A. Landman. “Characterizing Continuous and Discrete Hybrid Latent Spaces for Structural Connectomes”. SPIE Medical Imaging: Image Processing, February 2026. doi: 10.1117/12.3086529

  • Praitayini Kanakaraj, Lianrui Zuo, Gaurav Rudravaram, Tianyuan Yao, Zhiyuan Li, Yihao Liu, Nancy R. Newlin, Aravind Krishnan, Adam M. Saunders, Michael E. Kim, Baxter P. Rogers, L. Taylor Davis, Derek Archer, Kurt G. Schilling, Daniel Moyer, Bennett A. Landman, and Adam Anderson. “DETERMINATOR: Determinant Gradient Field Estimation for Accurate b-value Correction in Diffusion MRI”. SPIE Medical Imaging: Image Processing, February 2026. doi: 10.1117/12.3086531

  • Adam M. Saunders, Michael E. Kim, Kurt G. Schilling, John C. Gore, Bennett A. Landman, and Yurui Gao. “Vasculature-informed spatial smoothing of white matter functional magnetic resonance imaging”. SPIE Medical Imaging: Image Processing, February 2025. doi: 10.1117/12.3047240 Robert F. Wagner All-Conference Best Student Paper Finalist.

  • Adam M. Saunders, Gaurav Rudravaram, Nancy R. Newlin, Michael E. Kim, John C. Gore, Bennett A. Landman, and Yurui Gao. “A 4D atlas of diffusion-informed spatial smoothing windows for BOLD signal in white matter”. SPIE Medical Imaging: Image Processing, February 2025. doi: 10.1117/12.3047240

  • Elyssa McMaster, Lemuel Puglisi, Chenyu Gao, Aravind R. Krishnan, Adam M. Saunders, Daniele Ravi, Lori L. Beason-Held, Susan M. Resnick, Lianrui Zuo, Daniel Moyer, and Bennett A. Landman. “A technical assessment of latent diffusion for Alzheimer’s Disease progression”. SPIE Medical Imaging: Image Processing, February 2025. doi: 10.1117/12.3047135

  • Gaurav Rudravaram, Shunxing Bao, Aravind R. Krishnan, Lucas W. Remedios, Michael E. Kim, Adam M. Saunders, Qi Liu, Ken S. Lau, Joseph T. Roland, Mary K. Washington, Lori A. Coburn, Keith T. Wilson, Yuankai Huo, and Bennett A. Landman. “Identifying cellular neighborhood phenotypes differentiating normal and quiescent Crohn’s disease via MxIF”. SPIE Medical Imaging: Digital and Computational Pathology, February 2025. doi: 10.1117/12.3047121

  • Jessica Samir, Karthik Ramadass, Adam M. Saunders, Aravind Krishnan, Lucas Remedios, Elyssa McMaster, and Bennett A. Landman. “The Medical Segmentation Decathlon without a doctorate”. SPIE Medical Imaging: Clinical and Biomedical Imaging, February 2025. doi: 10.1117/12.3047076

  • Aravind R. Krishnan, Yihao Liu, Kaiwen Xu, Michael E. Kim, Lucas W. Remedios, Gaurav Rudravaram, Adam M. Saunders, Bradley W. Richmond, Kim L. Sandler, Fabien Maldonado, Bennett A. Landman, and Lianrui Zuo. “Investigating the impact of kernel harmonization and deformable registration on inspiratory and expiratory chest CT images for people with COPD”. SPIE Medical Imaging: Clinical and Biomedical Imaging, February 2025. doi: 10.1117/12.3048827

  • Adam Saunders, Sajal Dash, Aristeidis Tsaris, and Hong-Jun Yoon. “A comparison of histopathology imaging comprehension algorithms based on multiple instance learning”. SPIE Medical Imaging: Digital and Computational Pathology, February 2023. doi: 10.1117/12.2654265

  • Yimeng Dou, Adam M. Saunders, Andre T. S. Hucke, Michael E. Kim, Adam W. Anderson, Eric R. Tkaczyk, Bennett A. Landman, and Daniel Moyer. “DaFISH: Directionally Factorized Illumination with Spherical Harmonic Rotation”. Submitted to IEEE International Conference on Robotics & Automation, May 2027.

  • Ema Topolnjak, Gaurav Rudravaram, Michael E. Kim, Adam M. Saunders, Murat Bilgel, Lori L. Beason-Held, Derek B. Archer, Timothy J. Hohman, and Bennett A. Landman. “Restoring connectivity in tractography-derived structural connectomes with imputation”. Submitted to SPIE Medical Imaging: Image Processing, February 2027.

  • Ema Topolnjak, Gaurav Rudravaram, Adam M. Saunders, Trent M. Schwartz, Michael E. Kim, Malvika Viswanathan, Bennett A. Landman, and Zhongliang Zu. “Recovering model parameters from simulated Z-spectra through inverse modeling”. Submitted to SPIE Medical Imaging: Physics of Medical Imaging, February 2027.

  • Madison Sandler Rhodes, Gaurav Rudravaram, Aravind R. Krishnan, Lianrui Zuo, Adam M. Saunders, Wali Sidiqyar, Tyler J. Murphy, Mayur B. Patel, and Bennett A. Landman. “Introducing SPECTRA: Standardized Perceptual Encoding of Clinical Three-dimensional Representation of Anatomy”. Submitted to SPIE Medical Imaging: Clinical and Biomedical Imaging, February 2027.

  • Zhenhan Lin, Adam M. Saunders, Xiaoyue Liu, Trent Schwartz, Gaurav Rudravaram, Isaac Bakis, Melissa Goldin, Louise A. Mawn, and Bennett A. Landman. “Corrective refinement with cascaded nnU-Net for through-plane resolution harmonization in orbital CT segmentation”. Submitted to SPIE Medical Imaging: Clinical and Biomedical Imaging, February 2027.

  • Elyssa M. McMaster, Adam M. Saunders, Gaurav Rudravaram, Gabriella C. Taylor, Michael E. Kim, Aravind R. Krishnan, Bohan Jiang, Jongyeon Yoon, Lianrui Zuo, Laurie E. Cutting, Bennett A. Landman, and Daniel Moyer. “Your age bins are rubbish: Kernel-weighted white matter templates of early brain development”. Submitted to SPIE Medical Imaging: Image Processing, February 2027.

  • Gaurav Rudravaram, Lianrui Zuo, Ema Topolnjak, Michael E. Kim, Adam M. Saunders, Elyssa M. McMaster, Paula Diaz Trujillo, Ely E. Wesley, Colin D. McKnight, Pratik P. Pandharipande, Mayur B. Patel, Cayce Strength, Brenda T. Pun, Amelia W. Maiga, Robert S. Dittus, David A. Bennett, Julie A. Schneider, Konstantinos Arfanakis, The HABS-HD Study Team, Derek B. Archer, Timothy J. Hohman, Yelena Bodien, Daniel C. Moyer, Kurt G. Schilling, and Bennett A. Landman. “Generalizable field of view extension for diffusion MRI via conditional flow matching”. Submitted to SPIE Medical Imaging: Image Processing, February 2027.

  • Adam M. Saunders, Gaurav Rudravaram, Elyssa M. McMaster, Michael E. Kim, Trent Schwartz, Yimeng Dou, Lianrui Zuo, Adam W. Anderson, and Bennett A. Landman. “Neural fields for adaptive white matter microstructural modeling”. Submitted to SPIE Medical Imaging: Image Processing, February 2027.

  • Adam M. Sadriddinov, Adam M. Saunders, Trent Schwartz, Aravind R. Krishnan, Andre T. S. Hucke, Gaurav Rudravaram, Elyssa M. McMaster, Michael E. Kim, Lucas W. Remedios, Chenyu Gao, Ashwin Kishtagari, Michael R. Savona, and Bennett A. Landman. “Characterizing pretrained models and fusion methods for robust spleen segmentation”. Submitted to SPIE Medical Imaging: Image Processing, February 2027.

  • Xiaoyue Liu, Zhenhan Lin, Adam M. Saunders, Gaurav Rudravaram, Isaac Bakis, Melissa Goldin, Justin Shi, Louise A. Mawn, and Bennett A. Landman. “Multi-object topology-aware anatomical modeling for consistent orbital segmentation”. Submitted to SPIE Medical Imaging: Image Processing, February 2027.

  • Sam Bogdanov, Gaurav Rudravaram, Adam M. Saunders, Michael E. Kim, James LeFevre, Jack Charles, Stuti Jain, Soheil Kolouri, Matthew S. Schrag, and Bennett A. Landman. “A geometric-to-neural cascade for cerebral microbleed detection in susceptibility-weighted MRI”. Submitted to SPIE Medical Imaging, February 2027.

  • Adam M. Saunders, Michael E. Kim, Gaurav Rudravaram, Elyssa M. McMaster, Chloe Scholten, Sequoia Wade, Marselle Rasdall, Simon Vandekar, Tonia S. Rex, François Rheault, and Bennett A. Landman. “Quality assurance of the Federal Interagency Traumatic Brain Injury Research (FITBIR) database for multi-site MRI analysis”. Submitted to SPIE Medical Imaging: Clinical and Biomedical Imaging, February 2027.

Abstracts and Short Papers

  • Elyssa M. McMaster, Gaurav Rudravaram, Trent Schwartz, Adam M. Saunders, Kurt G. Schilling, and Bennett A. Landman. “Minutes Matter: A Consensus Framework for Optimizing Diffusion-Weighted MRI Acquisition and Analysis”. International Society for Tractography, 2026.

  • Wali Sidiqyar, Gaurav Rudravaram, Elyssa M. McMaster, Trent Schwartz, Adam M. Saunders, Kurt G. Schilling, and Bennett A. Landman. “Introducing SPINS: A shared public visualization library of neuroanatomical structures”. Medical Imaging with Deep Learning, 2026.

  • Elyssa M. McMaster, Nancy Newlin, Trent Schwartz, Adam M. Saunders, Gaurav Rudravaram, Yehyun Suh, Jongyeon Yoon, Michael Eugene Kim, Chloe Cho, Karthik Ramadass, Yihao Liu, Lianrui Zuo, Eleftherios Garyfallidis, Talia M. Nir, Neda Jahanshad, Kurt Schilling, Daniel Moyer, and Bennett Allan Landman. “Introducing Beyond FA: Crowdsourcing Imaging Biomarkers for Alzheimer’s Disease”. Medical Imaging with Deep Learning, 2025.

  • Adam M. Saunders, Elyssa M. McMaster, Chris Rorden, Johaan Kathilankal Jis, Minyi Sun, Adam Sadriddinov, Lukas VanTilburg, Michael Eugene Kim, Bennett Allan Landman, and Kurt Schilling. “OpenDIVE: Streamlining Tractography Visualization”. Medical Imaging with Deep Learning, 2025.

  • Adam M. Saunders, Kurt G. Schilling, Kristin P. O’Grady, Seth Smith, and Bennett A. Landman. “A maximum a posteriori method for quantitative T1 mapping with uncertainty using MP2RAGE”. International Society for Magnetic Resonance in Medicine, 2024.

  • Hong-Jun Yoon, Adam Saunders, Folami Alamudun, Sajal Dash, Jacob Hinkle, and Aristeidis Tsaris. “Ensemble learning of attention-based models for whole-slide imaging comprehension”. Computational Approaches for Cancer Workshop, 2022.

Talks

  • “Phenotype discovery of traumatic brain injury segmentations from heterogeneous multi-site data”. SPIE Medical Imaging: Image Processing, February 2026.

  • “DeepN4: Learning ITKN4 bias field correction for T1-weighted images”. DIPY Workshop, March 2025.

  • “A 4D atlas of diffusion-informed spatial smoothing windows for BOLD signal in white matter”. SPIE Medical Imaging: Image Processing, February 2025.

  • “Vasculature-informed spatial smoothing of white matter functional magnetic resonance imaging”. Vanderbilt University Institute of Imaging Science Retreat, October 2024.

  • “Deep learning for a healthier world: Detecting and grading diabetic retinopathy”. University of Dayton Honors Thesis Signature Talks at Stander Symposium, April 2023.

Professional Outreach

  • Reviewer, Medical Image Analysis (1 paper)
  • Reviewer, Journal of Medical Imaging (1 paper)
  • Reviewer, Scientific Reports (1 paper)
  • Secretary of VALIANT Attempt, Vanderbilt University, 2024 - Present

Honors and Awards

  • Outstanding Reviewer, International Workshop on Simulation and Synthesis in Medical Imaging at MICCAI, October 2026
  • Third Place, 3-minute Poster Competition, SPIE Medical Imaging, February 2026
  • Robert F. Wagner All-Conference Best Student Paper Finalist, SPIE Medical Imaging, February 2025
  • Second Place, 3-minute Poster Competition, SPIE Medical Imaging, February 2025
  • Graduate School Travel Grant, Vanderbilt University, November 2024
  • University Graduate Fellowship, Vanderbilt University, July 2024
  • Thomas R. Armstrong Award of Excellence for Outstanding Electrical Engineering Achievement, University of Dayton Department of Electrical and Computer Engineering, May 2023
  • Outstanding Collaborative Pianist, University of Dayton Department of Music, May 2023
  • Dean’s List, University of Dayton, August 2019 - May 2023
  • SPIE Travel Grant, February 2023
  • Best Poster in Directorate, Oak Ridge National Laboratory Summer Intern Symposium, August 2022
  • Honors Thesis Fellowship, University of Dayton, April 2022
  • Finalist, International Science and Engineering Fair, May 2018

Skills

  • Deep learning for medical imaging and data imputation using Python/PyTorch
  • Adept at statistical analysis and interpretation
  • Technical writing and typesetting using Microsoft Office
  • Effective scientific communication and visual aid preparation
  • Strong critical thinking and analytical skills