Jon Tamir, PhD
Assistant Professor
ECE, UT Austin

EER 7.872
2501 Speedway, Austin, TX 78712

Github / Google Scholar / LinkedIn / Twitter

I am recruiting students and post-docs for the next academic cycle, primarily interested in MRI pulse sequence design and image reconstruction. Please reach out if you would like to learn more: Link to flyer



I am an assistant professor in Electrical and Computer Engineering at The University of Texas at Austin, with a joint appointment in the Department of Diagnostic Medicine at the Dell Medical School. I received my PhD from UC Berkeley in 2018 and continued as a research associate in Electrical Engineering and Computer Sciences. My research focus spans computational magnetic resonance imaging, signal processing, and machine learning. I am primarily interested in applying advanced imaging and reconstruction techniques to pediatric MRI, with the goal of enabling real clinical adoption.

From May 2018 December 2019, I was a part-time research scientist at Subtle Medical.

In Winter 2016, I was a visiting scientist at GE Healthcare Israel, working with Yuval Zur. In Summer 2015 I interned at Arterys. Some time before that I interned at National Instruments. And way before that I interned at Centaur Technology.

I got my undergaduate degree in Electrical and Computer Engineering at UT Austin.

Research Overview

Unsupervised Deep Basis Pursuit: Learning without ground-truth data
> Prepint
> NeurIPS 2019 Poster
> ISMRM 2019 Slides

Fast, Targeted Pediatric Knee MRI Exam

Using T2 Shuffling in the clinic

T1-T2 Shuffling: Multi-Contrast 3D Fast Spin-Echo with T1 and T2 Sensitivity

T1-T2 Shuffling is an MRI acquisition and reconstruction method based on 3D Fast Spin-Echo, and extends T2 Shuffling. The method mitigates image blur and rerospectively synthesizes T1-weighted and T2-weighted volumetric images. By varying the repetition times (TR) accross the different echo trains, T1 sensitivity is encoded in the imaging data. The TR values are chosen based on maximizing Fisher Information for T1 estimation. A joint T1-T2 subspace is computed from an ensemble of simulated FSE signal evolutions, and linear combinations of the subspace coefficients are computed to generate synthetic T1-weighted and T2-weighted image contrasts.

T2 Shuffling: Sharp, Multi-Contrast, 3D Fast Spin-Echo MRI

T2 Shuffling is an MRI acquisition and reconstruction method based on 3D Fast Spin-Echo. The method accounts for temporal dynamics during the echo trains to reduce image blur and resolve multiple image contrasts along the T2 relaxation curve. The echo train ordering is randomly shuffled during the acquisition according to variable density Poisson disk sampling masks. The shuffling leads to reduced image blur at the cost of noise-like artifacts. The artifacts are iteratively suppressed in a regularized reconstruction based on compressed sensing, and the full signal dynamics are recovered.

Berkeley Advanced Reconstruction Toolbox (BART)

BART is a collection of tools for prototyping new MRI reconstruction methods and integrating them into the clinic.

Jan. 19, 2016: We gave a demo of BART at the 2016 ISMRM Workshop on Data Sampling and Image Reconstruction. You can find all the materials presented at the workshop, including quick installation steps and demo walkthroughs, here: Bart Workshop Materials

Logo credit: Michelle Tamir

Undergraduate Researchers

I like working with undergraduates on interesting projects. If you are interested, please contact me!

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