Rehman Ali
Professional Inverse Criminal at Large 😎
I am a computational imaging researcher working at the intersection of computational wave physics, inverse problems, and medical ultrasound imaging.
Background
I completed my M.S. in Computational and Mathematical Engineering in 2020, and my Ph.D. in Electrical Engineering in 2021, both from Stanford University, advised by Jeremy J. Dahl, Biondo L. Biondi, Peter K. Kitanidis, and John M. Pauly. My broad training in computational imaging spans a range of imaging disciplines including medical imaging, optics, remote sensing, and seismic imaging. In fact, my research in medical ultrasound directly draws from seismic imaging techniques, such as full-waveform inversion (FWI) and wave-equation migration velocity analysis (WEMVA), originally used to create images of the Earth. I am currently a postdoctoral fellow with Neb Duric in the Department of Imaging Sciences at the University of Rochester Medical Center (URMC) and currently supported by the NIH K99/R00 Pathway to Independence Award from the National Institute of Biomedical Imaging and Bioengineering (NIBIB) to establish an independent research program in computational ultrasound imaging.
Research Interests
My research focuses on developing wave-physics-based computational methods for the quantitative ultrasound imaging of tissue mechanical properties. I am particularly interested in using wave propagation models and inversion methods to improve the resolution, quantitative accuracy, and robustness of ultrasound tissue characterization for high-impact clinical applications. My current work develops computational imaging approaches for both transmission ultrasound tomography and pulse-echo ultrasound, including:
- Cycle-skipping-robust variants of FWI for transcranial ultrasound tomography
- Fast, scalable, and accurate 3D FWI models for whole-breast ultrasound tomography and breast cancer screening
- WEMVA for sound speed estimation and aberration correction in pulse-echo ultrasound
Open-Source Projects
A central goal of my research is to develop practical computational imaging methods that can translate advanced wave physics into medical imaging systems that address clinical needs. As an important steppingstone towards those long-term clinical goals, I develop and share open-source software tools and datasets to facilitate reproducible research in quantitative ultrasound imaging and inverse problems. My projects span:
- Sound Speed Estimation and Aberration Correction for Pulse-Echo Ultrasound
- Ultrasound Tomography (UST) Based on Ultrasound Transmission Through Tissue
- Full Wave Physics and Numerical Simulation Techniques
For publications, software, and additional research information, please explore the sections of this website, my GitHub repositories, or visit my Google Scholar profile.