Polina Golland
Sunlin (1966) and Priscilla Chou Professor
Develops statistical methods for biomedical image analysis, including shape modeling and characterizing biological processes from images.
Polina Golland's lab at MIT works on medical imaging & healthcare AI, genomics & computational biology and medical image analysis. 31 papers since 2023, 15 at top venues, mostly MICCAI and CVPR. 5 PhD students. 31 alumni. Applications close .
At a glance
- papers, 2023–2026
- 8/ year
- at T1 venues
- 48%
- PhD students
- 5
- MS students
- 0
- alumni listed
- 31
Papers by yearfrom DBLP, 2023–2026
- 1 papers2026 · T1 1 · collecting
- 10 papers2025 · T1 8
- 8 papers2024 · T1 3
- 12 papers2023 · T1 3
T1 venuesOtherVenues: MICCAI, CVPR, ICLR, NeurIPS, ECCV
Research focuspaper titles that use each topic's words
- Medical image analysis3 papers
- Medical imaging & healthcare AI2 papers
- Genomics & computational biology0 papers
- shape modeling0 papers
- biomedical image0 papers
Paper list
From DBLP.
20261 paper
202510 papers
- ICLR (T1)Calibrating Expressions of Certainty (opens in a new tab)
- NeurIPS (T1)Connecting Jensen-Shannon and Kullback-Leibler Divergences: A New Bound for Representation Learning (opens in a new tab)
- NeuroImageDeep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging (opens in a new tab)
- MICCAI (T1)Fetuses Made Simple: Modeling and Tracking of Fetal Shape and Pose (opens in a new tab)
- ICLR (T1)Learning General-purpose Biomedical Volume Representations using Randomized Synthesis (opens in a new tab)
- COLAS@MICCAIMulti-stage CNN for Fast Registration of 3D Preoperative CTs to 2D Intraoperative X-Rays (opens in a new tab)
- NeurIPS (T1)PolyPose: Deformable 2D/3D Registration via Polyrigid Transformations (opens in a new tab)
- MICCAI (T1)Robust Fetal Pose Estimation Across Gestational Ages via Cross-Population Augmentation (opens in a new tab)
- MICCAI (T1)Spatial Regularisation for Improved Accuracy and Interpretability in Keypoint-Based Registration (opens in a new tab)
- TPAMI (T1)Supervision by Denoising (opens in a new tab)
20248 papers
- WACVAnyStar: Domain randomized universal star-convex 3D instance segmentation (opens in a new tab)
- CVPR (T1)Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI (opens in a new tab)
- MLMI@MICCAIGeo-UNet: A Geometrically Constrained Neural Framework for Clinical-Grade Lumen Segmentation in Intravascular Ultrasound (opens in a new tab)
- ICML (T1)Implicit Representations via Operator Learning (opens in a new tab)
- CVPR (T1)Intraoperative 2D/3D Image Registration via Differentiable X-Ray Rendering (opens in a new tab)
- MIDLNetwork conditioning for synergistic learning on partial annotations (opens in a new tab)
- IEEE Trans. Medical ImagingSE(3)-Equivariant and Noise-Invariant 3D Rigid Motion Tracking in Brain MRI (opens in a new tab)
- PIPPI@MICCAISpaER: Learning Spatio-temporal Equivariant Representations for Fetal Brain Motion Tracking (opens in a new tab)
202312 papers
- NeuroImageAccurate Bayesian segmentation of thalamic nuclei using diffusion MRI and an improved histological atlas (opens in a new tab)
- MICCAI (T1)Boundary-Weighted Logit Consistency Improves Calibration of Segmentation Networks (opens in a new tab)
- PIPPI@MICCAIConsistency Regularization Improves Placenta Segmentation in Fetal EPI MRI Time Series (opens in a new tab)
- MIDLData Consistent Deep Rigid MRI Motion Correction (opens in a new tab)
- Trans. Mach. Learn. Res.Discretization Invariant Networks for Learning Maps between Neural Fields (opens in a new tab)
- MICCAI (T1)Domain-Agnostic Segmentation of Thalamic Nuclei from Joint Structural and Diffusion MRI (opens in a new tab)
- AMAI@MICCAIFeature Selection for Malapposition Detection in Intravascular Ultrasound - A Comparative Study (opens in a new tab)
- IEEE Trans. Medical ImagingNeSVoR: Implicit Neural Representation for Slice-to-Volume Reconstruction in MRI (opens in a new tab)
- MLHCSample-Specific Debiasing for Better Image-Text Models (opens in a new tab)
- IEEE Trans. Medical ImagingSpatial-Intensity Transforms for Medical Image-to-Image Translation (opens in a new tab)
- TOG (T1)Symmetric Volume Maps: Order-invariant Volumetric Mesh Correspondence with Free Boundary (opens in a new tab)
- IPMIUsing Multiple Instance Learning to Build Multimodal Representations (opens in a new tab)
Where alumni went31 listed
Apply to MITFall 2027
MIT EECS Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
- TOEFL/IELTS
- Fee
- USD 90
Confirmed on the program page.
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