DURHAM, NC · DUKE · BME
Rory Wu

§ 01 · Dispatch

I bring magnetic fields, math, and deep learning together to see inside the brain.

I'm Tianhe "Rory" Wu, a PhD student in Biomedical Engineering at Duke University. I work on quantitative MRI, MR fingerprinting, and reconstruction methods for understanding the brain through more reliable measurements.

Based

Durham, NC

Program

PhD · BME · Duke

Advisor

Dr. Dan Ma

Coords

36.00° N · 78.94° W

— MR Fingerprinting Quantitative MRI Pulse Sequence Design Image Reconstruction Deep Learning for Medical Imaging — MR Fingerprinting Quantitative MRI Pulse Sequence Design Image Reconstruction Deep Learning for Medical Imaging

§ 02 · Research

I’m interested in imaging methods that make the invisible measurable: how the brain behaves, how disease changes physiology, and how algorithms can make those signals easier to trust.

Right now, I’m especially focused on brain qMRI: using acquisition design, reconstruction, and modeling to estimate tissue properties more consistently across scans.

The goal is not only sharper images, but measurements that are easier to compare, explain, and use in downstream biomedical questions.

  • quantitative MRI
  • MR fingerprinting
  • brain mapping
  • image reconstruction
  • signal modeling
  • learning-based methods

§ 03 · Bio

I am a PhD student in Biomedical Engineering at Duke University, advised by Dr. Dan Ma.

My work sits at the intersection of quantitative MRI, MR fingerprinting, and learning-based reconstruction: building methods that turn complex MR signal behavior into measurements of brain tissue, physiology, and disease-related change.

Before Duke, I studied Applied Mathematics and Biology at Emory University. I’m drawn to work that combines careful modeling, useful algorithms, and clinically meaningful imaging questions.

§ 04 · Focus

  • 01
    MR Fingerprinting

    Acquisition and signal-modeling strategies for estimating tissue parameters from dynamic MR responses.

  • 02
    Quantitative MRI

    Methods that move MRI from qualitative contrast toward reproducible, comparable brain measurements.

  • 03
    Deep Learning for Medical Imaging

    Learning-based tools for reconstruction, denoising, and extracting stable information from complex imaging data.

§ 05 · Education

Ph.D. in Biomedical Engineering

Pratt School of Engineering, Duke University

2030 (Expected)

BS in Applied Mathematics & BA in Biology

College of Arts and Sciences, Emory University

2025

§ 06 · Fluency

— Research tools

  • Python
  • C++
  • Math

— Languages

  • English
  • Chinese
  • Latin

§ 08 · Reach out

Let’s compare signals.

I’m happy to talk about quantitative MRI, MR fingerprinting, deep learning in medical imaging, or adjacent research questions.

rory.wu@duke.edu