Unified Brain Surface and Volume Registration

S. Mazdak Abulnaga, Andrew Hoopes, Malte Hoffmann, Robin Magnet, Maks Ovsjanikov, Lilla Zollei, John Guttag, Bruce Fischl*, Adrian V. Dalca*. International Conference on Learning Representations (2026).

[Paper] [Abstract]

AtlasMorph: Learning conditional deformable templates for brain MRI

Marianne Rakic, Andrew Hoopes, S. Mazdak Abulnaga, Mert R Sabuncu, John V Guttag, Adrian V Dalca. Medical Image Analysis.

[Paper] [Abstract]

MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging Datasets with In-Context Guidance

Hallee E. Wong, Jose Javier Gonzalez Ortiz, John Guttag, Adrian V. Dalca. International Conference on Computer Vision (ICCV), 2025.

[Paper] [Abstract] [Website] [Code]

Classifying Phonotrauma Severity from Vocal Fold Images with Soft Ordinal Regression

Katie Matton, Purvaja Balaji, Hamzeh Ghasemzadeh, Jameson C. Cooper, Daryush D. Mehta, Jarrad H. Van Stan, Robert E. Hillman, Rosalind Picard, John Guttag, S. Mazdak Abulnaga. Machine Learning for Health.

[Paper] [Abstract] [Code]

CIRPIN: Learning Circular Permutation-Invariant Representations to Uncover Putative Protein Homologs

Aiden R. Kolodziej, S. Mazdak Abulnaga, Sergey Ovchinnikov. Machine Learning for Computational Biology (MLCB).

[Paper] [Abstract] [Website] [Code]

Faraday Cage Estimation of Normals for Point Clouds and Ribbon Sketches

Daniel Scrivener, Daniel Cui, Ellis Coldren, S. Mazdak Abulnaga, Mikhail Bessmeltsev, Edward Chien. ACM Transactions on Graphics/SIGGRAPH 2025.

[Paper] [Abstract] [Website] [Code]

Schwarz-Schur Involution: Lightspeed Differentiable Sparse Linear Solvers

Yu Wang, S. Mazdak Abulnaga, Yael Balbastre, Bruce Fischl. International Conference on Machine Learning (ICML) 2025.

[Paper] [Abstract] [Code] [Poster]

MultiMorph: On-demand Atlas Construction

S. Mazdak Abulnaga, Andrew Hoopes, Neel Dey, Malte Hoffmann, Bruce Fischl, John Guttag, Adrian V. Dalca. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025.

[Paper] [Abstract] [Website] [Code]

ScribblePrompt: Fast and Flexible Interactive Segmentation for Any Biomedical Image

Hallee E. Wong, Marianne Rakic, John Guttag, Adrian V. Dalca. European Conference on Computer Vision (ECCV) 2024.

[Paper] [Abstract] [Website] [Code] [Video] [Demo]

Quantifying disparities in intimate partner violence: a machine learning method to correct for underreporting

Divya Shanmugam, William Hou, Emma Pierson. npj Women's Health 2024.

[Paper] [Abstract]

Tyche: Stochastic In-Context Learning for Medical Image Segmentation

Marianne Rakic, Hallee E. Wong, Jose Javier Gonzalez Ortiz, Beth Cimini, John Guttag, Adrian V. Dalca. EEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2024.

[Paper] [Abstract] [Website] [Code] [Video]

AnyStar: Domain randomized universal star-convex 3D instance segmentation

Neel Dey, S. Mazdak Abulnaga, Benjamin Billot, Esra Abaci Turk, P. Ellen Grant, Adrian V. Dalca, Polina Golland. IEEE Winter Applications on Computer Vision (WACV) 2024.

[Paper] [Abstract] [Code]

Shape-aware Segmentation of the Placenta in BOLD Fetal MRI Time Series

S. Mazdak Abulnaga, Neel Dey, Sean I. Young, Katherine Hobgood, Eileen Pan, Clinton J. Wang, P. Ellen Grant, Esra Abaci Turk, Polina Golland. Machine Learning for Biomedical Imaging (MELBA), 2023.

[Paper] [Abstract] [Code]

Scale-Space Hypernetworks for Efficient Biomedical Imaging

Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca. NeurIPS 2023.

[Paper] [Abstract] [Code]

Coarse race data conceals disparities in clinical risk score performance

R. Movva*, D. Shanmugam*, K. Hou, P. Pathak, J. Guttag, N. Garg, E. Pierson. MLHC 2023.

[Paper] [Abstract] [Code]

GIST: Generating Image-Specific Text for Fine-grained Object Classification

Kathleen M Lewis*, Emily Mu*, Adrian Dalca, John Guttag. Preprint.

[Paper] [Abstract] [Code]

UniverSeg: Universal Medical Image Segmentation

Victor Ion Butoi*, Jose Javier Gonzalez Ortiz*, Tianyu Ma, Mert R. Sabuncu, John Guttag, Adrian V. Dalca. International Conference on Computer Vision (ICCV) 2023.

[Paper] [Abstract] [Code]

Magnitude Invariant Parametrizations Improve Hypernetwork Learning

Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca. Preprint.

[Paper] [Abstract] [Code]

At the Intersection of Conceptual Art and Deep Learning: The End of Signature

Kathleen M Lewis, Divya M Shanmugam, Jose Javier Gonzalez Ortiz, Agnieszka Kurant, John Guttag. NeurIPS 2022 WBRC Workshop.

[Paper] [Abstract] [Slides]

SizeGAN: Improving Size Representation in Clothing Catalogs

Kathleen M Lewis, John Guttag. Preprint.

[Paper] [Abstract]

SynthStrip: Skull-Stripping for Any Brain Image

A. Hoopes, J. Mora, A. Dalca, B. Fischl, M. Hoffmann. NeuroImage 2022.

[Paper] [Abstract] [Code] [Video]

Learning to Limit Data Collection via Scaling Laws: A Computational Interpretation for the Legal Principle of Data Minimization

D. Shanmugam, F. Diaz, S. Shabanian, M. Finck, A. Biega. FAccT 2022.

[Paper] [Abstract]

Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs

Harini Suresh, Kathleen M Lewis, John Guttag, Arvind Satyanarayan. International Conference on Intelligent User Interfaces (IUI) 2022.

[Paper] [Abstract]

Learning the Effect of Registration Hyperparameters with HyperMorph

A. Hoopes, M. Hoffmann, D. Greve, B. Fischl, J. Guttag, A. Dalca. MELBA 2022.

[Paper] [Abstract] [Code] [Video]

Better Aggregation for Test-Time Augmentation

D. Shanmugam, D. Blalock, G. Balakrishnan, J. Guttag. ICCV 2021.

[Paper] [Abstract] [Slides] [Poster]

TryOnGAN: Body-Aware Try-On via Layered Interpolation

Kathleen M Lewis, Srivatsan Varadharajan, Ira Kemelmacher-Shlizerman. ACM Transactions on Graphics (TOG) 2021.

[Paper] [Abstract]

Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings

Amy Zhao, Guha Balakrishnan, Kathleen M Lewis, Frédo Durand, John V Guttag, Adrian V Dalca. CVPR 2020.

[Paper] [Abstract] [Code]

Fast Learning-based Registration of Sparse 3D Clinical Images

Kathleen M Lewis, Natalia S Rost, John Guttag, Adrian V Dalca. ACM Conference on Health, Inference, and Learning (CHIL) 2020.

[Paper] [Abstract]

What is the State of Neural Network Pruning?

Jose Javier Gonzalez Ortiz*, Davis Blalock*, Jonathan Frankle, John Guttag. MLSys 2020.

[Paper] [Abstract] [Code] [Slides] [Poster]

Multiple Instance Learning for ECG Risk Stratification

D. Shanmugam, D. Blalock, J. Guttag. MLHC 2019.

[Paper] [Abstract] [Slides] [Poster]

Learning from Few Subjects with Large Amounts of Voice Monitoring Data

Jose Javier Gonzalez Ortiz, Daryush Mehta, Jarrad Van Stan, Robert Hillman, John Guttag, Marzyeh Ghassemi . Machine Learning for Healthcare 2019.

[Paper] [Abstract]