The LDR Group at JHU conducts interdisciplinary research in AI, with a focus on Machine Learning, Computer Vision, and Healthcare & Biomedical Applications. We develop data-driven methods that transform data into actionable intelligence, covering the full spectrum from learning patterns in complex data, to discovering novel and meaningful insights, and ultimately reasoning for informed decision-making.
With the ultimate goal of advancing healthcare outcomes, we care about: - Developing foundational theories in machine learning, and practical algorithms for healthcare & biomedical applications; - Translating our scientific discoveries from the bench to real-world impact at the bedside.
Our work covers a wide range of disciplines. Naturally, we publish in top venues ranging from computer vision (e.g., CVPR, ICCV, ECCV) and machine learning (e.g., NeurIPS, ICLR, ICML) conferences, to medical conferences and journals (e.g., MICCAI, IPMI, IEEE TMI).
★★ If you are interested in joining us, please check out our openings ★★
News
[Upcoming MICCAI26 Challenge — FOMO] We will host the 2nd FOMO Challenge (foundation model challenge for Brain MRI) at MICCAI 2026. To joined our challenge, check out FOMO26’s official website here.
2026
06.18 ~ Congratulations to Jun for her paper accepted at ECCV 2026: “Physics-Grounded Disentangled Flow Modeling for Brain Disease Progression Trajectory'' [pdf][code]
06.12 ~ Congratulations to Yi-Chen (Matthew) for his paper accepted at MICCAI 2026: “HemoPIC: A Physics-Informed Cerebral Hemodynamics Digital Twin for Brain Perfusion'' [pdf][code]
06.07 ~ Peirong served as Medical Vision Oral Session Chair at CVPR 2026.
06.04 ~ We hosted “Recent Advances in AI for Medical Imaging: Progress, Challenges, and Future Directions'' at CVPR 2026 Tutorial, check our latest progress on “Physics-Driven Learning for Interpretable Medical AI'' [slides]
05.20 ~ Peirong was recognized as Outstanding Area Chair at CVPR 2026.
04.01 ~ Peirong served as Area Chair at NeurIPS 2026.
01.26 ~ Peirong served as Area Chair at MICCAI 2026.
2025
12.01 ~ Check out our new work, on unifying the bidirectional generation and editing of pathology-healthy brain imaging [pdf][code]
09.18 ~ We received 4 x RTX PRO 6000 Blackwell GPU NVIDIA Academic Grant to support our research on physics-informed deep learning.
08.20 ~ Peirong served as Area Chair at ICLR 2026 and CVPR 2026.
07.20 ~ Check out our preprint for FOMO-60k (a large-scale heterogeneous 3D brain MRI dataset) here.
07.16 ~ One paper accepted at MICCAI Deep Generative Models Workshop (DGM4MICCAI) 2025: “Conditional diffusion models for guided anomaly detection in brain images using fluid-driven anomaly randomization'' [pdf]
07.01 ~ Peirong joined JHU as an Assistant Professor in the Dept. of Electrical and Computer Engineering (ECE) and Data Science and Artificial Intelligence Institute (DSAI).
04.01 ~ We will host FOMO - the first foundation model challenge for Brain MRI - at MICCAI 2025. To joined our challenge, check out FOMO's official website here.
03.01 ~ Peirong served as Area Chair at MICCAI 2025.
02.26 ~ One paper accepted at CVPR 2025: “Unraveling Normal Anatomy via Fluid-Driven Anomaly Randomization'' [pdf][code]
01.22 ~ One paper accepted at ICLR 2025: “Hierarchical uncertainty estimation for learning-based registration in neuroimaging'' [pdf][code]
Older news (2018–2024)
2024
09.09 ~ Peirong was named as a Rising Star in Data Science by UCSD, UChicago, and Stanford.
08.16 ~ Peirong was named as a Rising Star in EECS by MIT.
07.12 ~ Peirong received the NIH Award at MICCAI 2024.
07.01 ~ One paper accepted at ECCV 2024: “Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging'' [pdf][code]
06.20 ~ Peirong started as a volunteer research mentor for Talaria Summer Institute.
06.17 ~ One paper accepted at MICCAI 2024: “PEPSI: Pathology-Enhanced Pulse-Sequence-Invariant Representations for Brain MRI'' [pdf][code]
02.02 ~ One paper accepted as Oral at ISBI 2024: “Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI'' [pdf][FreeSurfer]
2023
08.13 ~ Peirong joined as a postdoctoral researcher at Harvard Medical School and Massachusetts General Hospital.
2022
05.13 ~ Peirong joined as a research intern at Meta AI’s Computer Vision team for Summer 2022.
03.02 ~ One paper accepted as Oral at CVPR 2022: “Deep Decomposition for Stochastic Normal-Abnormal Transport'' [pdf][code]
2021
09.28 ~ One paper accepted at NeurIPS 2021: “Accurate Point Cloud Registration with Robust Optimal Transport'' [pdf][code]
07.13 ~ One paper accepted at ICCV 2021: “Local Temperature Scaling for Probability Calibration'' [pdf][code]
05.13 ~ One paper accepted at IEEE TMI: “Perfusion Imaging: An Advection Diffusion Approach'' [pdf][code]
03.22 ~ Peirong joined as a research intern at Facebook AI’s Computer Vision team for Summer 2021.
03.13 ~ One paper accepted as Oral at CVPR 2021: “Discovering Hidden Physics Behind Transport Dynamics'' [pdf][code]
2020
08.15 ~ Peirong received the Student Travel Award at MICCAI 2020.
06.13 ~ One paper accepted at MICCAI 2020: “Fluid Registration Between Lung CT and Stationary Chest Tomosynthesis Images'' [pdf][code]
05.13 ~ One paper Early accepted as Oral at MICCAI 2020: “PIANO: Perfusion Imaging via Advection-Diffusion'' [pdf][code]
2019
06.02 ~ Peirong received the IPMI Scholarship at IPMI 2019.
02.26 ~ One paper accepted as Oral at IPMI 2019: “Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces'' [pdf][code]
Research Topics
Here are some of our currently ongoing topics. Based on your interests, we will work together to design your research project.
-> Machine Learning & Computer Vision:
- Generative Models; Representation Learning
- Physics-informed Deep Learning; Spatiotemporal Modeling
- Anomaly Detection; Uncertainty Estimation
-> Medical Image Analysis:
- Medical Digital Twins
- Multimodal and Longitudinal Modeling
- Generation; Reconstruction; Detection; Segmentation
-> Clinical Applications:
- Structural and Functional Brain Imaging (e.g., MRI, fMRI, CT)
- Cerebrovascular Flow Imaging (e.g., Perfusion Imaging, Angiography)
- Clinical Decision Making; Treatment Simulation and Planning
Selected Publications
( student mentee; full list on Google Scholar )
Jun Wang and Peirong Liu
ECCV, 2026
paper / code
Yi-Chen Lee and Peirong Liu
MICCAI, 2026
paper / code
Jun Wang and Peirong Liu
Tech report, 2026
paper / code
Peirong Liu, Ana Lawry Aguila, Juan Eugenio Iglesias
CVPR, 2025
paper / code
Xiaoling Hu, Karthik Gopinath, Peirong Liu, Malte Hoffmann, Koen Van Leemput, Oula Puonti, Juan Eugenio Iglesias
ICLR, 2025
paper / code
Peirong Liu, Oula Puonti, Annabel Sorby-Adams, William Taylor Kimberly, Juan Eugenio Iglesias
MICCAI, 2024
paper / code
Peirong Liu, Oula Puonti, Xiaoling Hu, Daniel C. Alexander, Juan Eugenio Iglesias
ECCV, 2024
paper / code
Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer
CVPR, 2022 (Oral - 4%)
paper / code
Peirong Liu, Lin Tian, Yubo Zhang, Stephen R. Aylward, Yueh Z. Lee, Marc Niethammer
CVPR, 2021 (Oral - 3.7%)
paper / code
Zhengyang Shen, Jean Feydy, Peirong Liu, Ariel Hernán Curiale, Ruben San José Estépar, Raúl San José Estépar, Marc Niethammer
NeurIPS, 2021
paper / code
Zhipeng Ding, Xu Han, Peirong Liu, Marc Niethammer
ICCV, 2021
paper / code
Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer
IEEE Transactions on Medical Imaging (TMI), 2021
paper / code
Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer
MICCAI, 2020 (Oral, Early Accept - 13%)
paper / code
Peirong Liu, Zhengwang Wu, Gang Li, Pew-Thian Yap, Dinggang Shen
IPMI, 2019 (Oral - 10%)
paper / code