RSL Researchers Earn Doctoral Degrees
Congratulations, you made it!
October 22, 2024
Yirong Yang, Department of Electrical Engineering
Adam S. Wang, advisor
Utilizing Spectral Information from Photon Counting CT
September 23, 2024
Laurel Hales, Department of Electrical Engineering
Feliks Kogan, advisor
Novel MRI Techniques for Imaging Microstructure, Inflammation, and Joint Dysfunction in the Knee
September 6, 2024
Louis Blankemeier, Department of Electrical Engineering
Akshay Chaudhari, advisor
Using AI to expand the clinical utility of 3D computed tomography imaging
August 12, 2024
Gustavo Ramon Chau Loo Kung, Department of Electrical Engineering
Jennifer McNab, Advisor
Quantifying Brain Microstructure with Multi-modal MRI in Epilepsy
May 28, 2024
Kasra Naftchi-Ardebili, Department of Bioengineering
Kim Butts Pauly, advisor
Transcranial Ultrasound Stimulation: Optimizing Simulation Paradigms and Modulation of the Neurons
May 24, 2024
David van Veen, Department of Electrical Engineering
John Pauly and Akshay Chaudhari, advisors
Date-Efficient Machine Learning for Image Reconstruction and Text Summarization in Biomedicine
May 22, 2024
Juan Manuel Zambrano Chaves, Department of Biomedical Data Science
Daniel Rubin, Akshay Chaudhari and Curt Langlotz, advisors
Development and Evaluation of Representations of Unstructured Radiology Data
April 11, 2024
Jiahong Ouyang, Department of Electrical Engineering
Greg Zaharchuk and Kilian M. Pohl, Advisors
Multi-dimensional Neuroimage Analysis
June 22, 2023
Arjun Desai, Department of Electrical Engineering
Akshay Chaudhari and Chris Re, Advisors
Principles for Machine Learning Systems in MRI: From Development to Deployment
June 1, 2023
Fikunwa Kolawole, Department of Mechanical Engineering
Daniel Ennis, advisor
MRI-driven Evaluation of Passive Myocardial Stiffness
February 14, 2023
Ningrui Li, Department of Electrical Engineering
Kim Butts Pauly, Advisor
Through thick and thin: improved transcranial focused ultrasound transmission estimates with acoustic simulation and magnetic resonance imaging
January 31, 2023
Mackenzie Carlson, Department of Bioengineering
Michelle James, Advisor
Development, Evaluation, and Translation of Novel Neuroimaging Probes and Techniques to Investigate Neurodengenerative Diseases
August 18, 2022
Beliz Gunel, Department of Electrical Engineering
John Pauly, Advisor
Leveraging Prior Knowledge and Structure for Data-Efficient Machine Learning
June 6, 2022
Elizabeth Cole, Department of Electrical Engineering
John Pauly, Advisor
Deep Learning for Accelerated MR Image Reconstruction
December, 2021
Jonathan Goodman, Department of Biophysics, MD-PhD program
Gary Glover, Advisor
Resolving Functional Landmarks in the Human Thalamus
March 23, 2022
Leandra Brickson, Department of Electrical Engineering
Jeremy Dahl, Advisor
Real-Time Reverberation Noise Suppression in Ultrasound Channel Signals Using a Fully Convolutional Neural Network
December, 2021
Jeffrey Wang, Department of Biophysics
Raag Airan, Advisor
Mapping the Whole-Brain Response to Noninvasive Neuromodulation: From Rodents to Humans
November, 2021
Rehman Ali, Department of Electrical Engineering
Jeremy Dahl, advisor
Sound Speed Estimation and Phase Aberration Correction in Medical Ultrasound Imaging
November, 2021
Patricia Lan, Department of Bioengineering
Gary Glover, advisor
Methods for imaging brain function using BOLD and viscoelastic contrast
April 21, 2022
Philip Kenneth Lee, Department of Electrical Engineering
Brian Hargreaves, Advisor
Robust Body Diffusion Magnetic Resonance Imaging
November, 2021
Hollis Crowder, Department of Mechanical Engineering
Marc Levenston, Advisor
Exploring structure-function relationships of knee cartilage and meniscus using medical imaging and soft tissue biomechanics techniques
September, 2021
Phillip DiGiacomo, Department of Bioengineering
Norbert Pelc and Michael Zeineh, Advisors
Validation and development of iron as an imaging-based biomarker ofneuroinflammation in Alzheimer's Disease
May, 2021
Mary Elizabeth Hall, Department of Mechanical Engineering
Marc Levenston, Advisor
Contrast Agent Diffusion as a CT Arthrography Biomarker for Articular Cartilage Health
May, 2021
Christopher Sandino, Department of Electrical Engineering
Shreyas Vasanawala, Advisor
Accelerating pediatric magnetic resonance imaging using deep learning-based reconstruction
July, 2020
Sarah Divel, Department of Electrical Engineering
Norbert Pelc, Advisor
The Validation and Optimization of CT Perfusion for Stroke Assessment
April, 2021
Lauren Watkins, Department of Bioengineering
Marc Levenston, Feliks Kogan, Advisors
Imaging strategies for quantitative, whole-joint assessment ofstructure and function related to knee osteoarthritis
November, 2020
Steve Leung, Department of Bioengineering
Kim Butts Pauly, Advisor
Leveraging simulations to improve focused ultrasound brain treatments
June, 2020
Steffi Perkins, Department of Bioengineering
Brian Hargreaves, Advisor
A Mixed-Reality System for Breast Surgical Planning in the Operating Room: Magnetic Resonance Imaging Development and Initial Clinical Evaluation
May, 2020
Seul Lee, Department of Electrical Engineering
Gary Glover, Advisor
Functional MRI Characterization of Lesion-Induced Plasticity and Improved Acquisition Techniques
June, 2019
Marrianne Black, Department of Mechanical Engineering
Prof. Marc Levenston, Advisor
Co-Advisors: Profs. Brian Hargreaves and Garry Gold
Quantitative Imaging of Cartilage and Meniscus for Early Detection of Osteoarthritis
June, 2019
Keshav Datta, Department of Electrical Engineering
Daniel Spielman, Advisor
Novel techniques for metabolic imaging using hyperpolarized carbon-13 compounds
May, 2019
Feiyu Chen, Department of Electrical Engineering
John Pauly, Advisor
Fast Motion-Robust Magnetic Resonance Imaging
April, 2019
Grant Yang, Department of Electrical Engineering
Jennifer McNab, Advisor
Diffusion Encoding Waveform Design for Mapping Microstructure in the Human Brain
February, 2019
Picha Shunhavanich, Department of Bioengineering
Norbert J. Pelc, Advisor
Challenges in CT with photon counting detectors
January, 2019
Mihir Pendse, Department of Electrical Engineering
Brian Rutt, Advisor
Managing Local SAR and B1+ Inhomogeneity in Ultra High Field MRI Using Parallel Transmission