Biomedical Engineering

Judith Su is an Assistant Professor in Biomedical Engineering and an Assistant Professor of Optical Sciences at the University of Arizona. She is also an Associate Member of the University of Arizona Cancer Center. Judith received her B.S. and M.S. from MIT in Mechanical Engineering and her Ph.D. from Caltech in Biochemistry & Molecular Biophysics. Her background is in imaging, microfabrication, and optical instrument building for biological and medical applications. In general, her research interests are to develop new imaging, sensing, and rheological techniques to reveal basic biological functions at the molecular, cellular, and tissue levels. Recently her work has centered on label-free single molecule detection using microtoroid optical resonators with a focus on basic research, and translational medicine through the development of miniature field portable devices.

Marek Romanowski, PhD, and his work on translating physics into medical products have huge implications for the evolution of personalized medicine. On cue, a tiny pillbox of gold floating in your bloodstream can deliver its medicine exactly to the right cell, one that is sick with cancer, avoiding all of your healthy cells. A gold capsule – about 50 to 200 nanometers in diameter, large enough to do the work of transporting a few molecules of medicine and respond to light signals – is too large to pass out through the kidneys. But on command by an enzyme, it can fall apart into pieces smaller than 10 nanometers, just a few molecules. The new size can easily leave our bodies at no risk. The gold pillbox has many other possible applications. In addition to delivering a drug, it can become a part of a diagnostic test, or deliver genetic material to a cell to permanently modify the cells’ DNA—a key step in gene therapy.

I am an MR physicist with extensive expertise in fast image acquisition methodology, pulse sequence design, and artifact correction for neuro MRI. In the past 18 years, I have developed novel approaches effectively addressing various types of challenging MRI artifacts, ranging from echo-planar imaging (EPI) geometric distortions, to susceptibility effect induced signal loss, to EPI Nyquist artifact, to motion-induced phase errors and aliasing artifacts in interleaved EPI based diffusion-weighted imaging. I am the original developer of multiplexed sensitivity encoded (MUSE) MRI, which can measure human brain connectivity in vivo at high spatial-resolution and accuracy, as shown in the publications listed below. More generally, my research involves the application of MR protocols in translational contexts. I have served as PI on NIH-funded R01, R21 and R03 grants, and have had extensive experience as a co-investigator on NIH-funded projects. The current focus of my research includes: * Development of high-throughput and motion-immune clinical MRI for imaging challenging patient populations * Imaging of neuronal connectivity networks for studies of neurological diseases * High-fidelity and multi-contrast MRI guided intervention * Characterization and correction of MRI artifacts * Signal processing and algorithm development * MRI studies of human development

Ali Bilgin, PhD, is an Associate Professor of Biomedical Engineering, Electrical and Computer Engineering, and Medical Imaging at the University of Arizona. Dr. Bilgin received the B.S. degree in electronics and telecommunications engineering from Istanbul Technical University, Istanbul, Turkey, M.S. degree in electrical engineering from San Diego State University, San Diego, CA, and Ph.D. degree in electrical engineering from the University of Arizona, Tucson, AZ.Dr. Bilgin’s research interests are in the areas of signal and image processing, and include image and video coding, data compression, and magnetic resonance imaging. He has authored/ co-authored over 250 research papers in these areas and has twelve granted and several pending patents. Dr. Bilgin was on the organizing committees of numerous conferences, and was an Associate Editor of the IEEE Signal Processing Letters from 2010 to 2012, the IEEE Transactions on Image Processing from 2010 to 2014, and the IEEE Transactions on Computational Imaging from 2014 to 2019.