Peirong Liu

Incoming Assistant Professor in ECE & DSAI @ Johns Hopkins University | PhD in CS @ UNC-Chapel Hill

★★ Starting in Fall 2025, I will join the Department of Electrical and Computer Engineering (ECE) and the Data Science and AI Institute (DSAI) at the Johns Hopkins University (JHU) as a tenure-track assistant professor. If you are interested in working with me, please follow the application instructions here. ★★

My name is Peirong Liu (刘沛榕), I am a postdoctoral researcher at Harvard Medical School & Massachusetts General Hospital, hosted by Dr. Juan Eugenio Iglesias. I received my PhD in Computer Science from UNC-Chapel Hill in 2023, where I was beyond fortunate to work with my incredible advisor, Dr. Marc Niethammer. During my PhD, I spent two wonderful summers as a research intern at Meta AI in New York City. I was recognized as a Rising Star in EECS by MIT, and a Rising Star in Data Science by UCSD, UChicago and Stanford. I was on the academic job market during the 2024-2025 cycle, here are my research statement and job talk slides (open with Adobe Reader to enable animations).

My research interests broadly lie in AI for Healthcare, at an intersection of machine learning (ML), computer vision (CV), and medical image computing (MIC), aiming to advance foundational theories for learning and representation, and establish general frameworks that support complex real-world systems.

ML/CV Theory & Algorithms: Physics-informed Deep Learning; Spatiotemporal Modeling; Representation Learning; Generative Modeling
Interdisciplinary MIC: Modality-agnostic Multi-task foundation Models in Medical Imaging; Image Generation, Reconstruction, Segmentation, Registration
Clinical Applications: Brain Perfusion; Stroke Diagnosis; Lesion Detection and Segmentation; Low-field MRI

[My Research Overview] - Motivated by real-world applications, I leverage my interdisciplinary expertise in machine learning, computer vision, and mathematics, to support various application areas. I strive for foundational approaches that provide interpretability and efficiency, ultimately applying them for practical challenges.

News

2025

04.01 ~ We will host FOMO - the first foundation model challenge for Brain MRI - at MICCAI 2025. To join our challenge, check out FOMO's official website here.

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]

2024

09.09 ~ Named as a Rising Star in Data Science by UCSD, UChicago, and Stanford.

08.16 ~ Named as a Rising Star in EECS by MIT.

07.12 ~ 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 ~ Start 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 ~ Join as a postdoctoral researcher in Athinoula A. Martinos Center for Biomedical Imaging at Harvard Medical School and Massachusetts General Hospital.

06.15 ~ Successfully defended my dissertation at UNC-Chapel Hill, I am officially a PhD now!

2022

05.13 ~ Join 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 ~ Join 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 ~ 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 ~ 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]