Learning, Discovery, Reasoning (LDR) Group

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, and (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 & Applied Mathematics:
    • Physics-informed Learning; Spatiotemporal Modeling; Differential Equations; Fluid Dynamics
    • Generative AI; Representation Learning; Anomaly Detection; Uncertainty Estimation
    • Geometric Deep Learning; Differential Geometry; Shape Analysis
  • Computer Vision & Medical Image Computing:
    • Multi-modal Multi-task Foundation Models in Medical Imaging
    • Image and Surface Generation, Reconstruction, Segmentation, Registration
    • Lesion Detection and Segmentation
  • Clinical Applications:
    • Brain Perfusion; Diffusion MRI; Functional MRI; Cortical Surface
    • Cardiovascular and Cerebrovascular Diseases
    • Disease Diagnosis; Treatment Planning; Interventional Surgery

Openings

I am looking for self-motivated students with solid mathematical background and strong coding skills in machine learning. Research experience in healthcare and biomedical applications is a plus, but not required. To ensure I don't miss your email, please first fill out your background information in this Google form.

Email: peirong9726[at]gmail.com
(Apologies for not being able to reply to every email due to the high volume. I will carefully review all submissions and reach out to shortlisted candidates.)

-> Prospective PhD: I have multiple openings for fully-funded PhD students, starting in Fall 2025 or 2026. If interested, please email me your CV, transcripts, as well as a brief summary on your background and research interests (Subject: "Prospective PhD").

-> Current PhD / MS / Undergrad: If you are at JHU and are looking for potential advisors, please email me directly (Subject: "JHU Student").

-> Prospective Postdoc: If interested, please email me your CV and a research statement (maximum 4 pages) (Subject: "Prospective Postdoc").

-> Prospective RA / Intern: Self-motivated interns are always welcome to join our group, with preference given to students interested in pursuing a PhD with me at JHU. If interested, please email me your CV and research interests (Subject: "Prospective RA / Intern").