LDR Group @ JHU

The JHU LDR group conducts interdisciplinary research in AI, with a focus on Machine Learning, Computer Vision, and Healthcare & Biomedical Applications. Our research is inspired by the charms and curses from the diverse and imperfect real-world data, which spans various forms (e.g., images, videos, text, voice, signals) and scales (e.g., molecules, cells, organs, individuals, populations). However, data alone is just a static archive, its true power emerges only when properly interpreted, analyzed, and applied. 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:
(1) Developing foundational theories in machine learning, and practical algorithms for healthcare & biomedical applications;
(2) 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).

Research Topics

Here are some topics that I am particularly interested in. Based on your interests, we will work together to design your research project after you join our group.

Machine Learning & Computer Vision:

Generative Models; Representation Learning
Physics-informed Learning; Spatiotemporal Modeling
Anomaly Detection; Uncertainty Estimation

Medical Image Analysis:

Image Generation; Reconstruction
Detection; Segmentation; Registration
Multimodal Modeling; Medical Foundation Models

Clinical Applications:

Structural Brain Imaging (MRI, CT); Functional MRI (fMRI)
Clinical Decision Making and Treatment Planning
Disease Diagnosis and Progression Modeling

Openings

* Please Read Below First *

Email: peirong[at]jhu.edu - The best way to get in touch with me is by emailing me directly.
Meet: Clark Hall 201B / Online - I prefer meetings scheduled by email appointment.
Logistics - I will make sure to review every application. However, due to the large volume of emails I receive, I am only able to respond to and interview shortlisted candidates whom I believe are a good fit.

-> Prospective PhD:

- If you are interested in a PhD position starting in Fall 2027, please email me your CV and selected publications (Subject: "Prospective PhD 2027").

- Expectations: I am looking for self-motivated PhD students with solid mathematical background and strong coding skills in machine learning and computer vision. Publication record in top-tier ML/CV venues (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICML) is highly preferred. Research experience in healthcare and biomedical applications is a plus, yet not required.

-> Current JHU Student:

- If you are an undergraduate or MS student at JHU looking for a faculty advisor for research, please email me your CV, and a short description of your research experience and interests (Subject: "JHU Student").

- Expectations: Please note that due to limited bandwidth, I am only able to take on students whose backgrounds align closely with our ongoing research projects.

-> Prospective Intern: If you are interested in joining us as an intern or short-term visitor, please email me your CV and research interests (Subject: "Prospective Intern").