Cheek, Eric
Machine learning methods for SPECT imaging
2020 Rackam Merit Fellow
On leave, working at KLA in Ann Arbor, starting W22
Hu, Jason
Image reconstruction
Murthy, Naveen
CT reconstruction algorithms, quantitative MRI
Gao, Mingjie
DBT using machine learning methods
(co-chaired with HP Chan, Radiology)
Jia, Yixuan (Isaac)
SPECT imaging
using machine learning methods
(co-advised with Yuni Dewaraja, Radiology)
Jones, Robert
MRI
(co-chaired with James Balter and Yue Cao, Radiation Oncology)
Li, Zongyu
SPECT and PET imaging
using machine learning methods
(co-advised with Yuni Dewaraja, Radiology)
Murguia, Amaya
Computational neuroscience
(co-advised with Jon-Nielsen, Radiology)
Salazar Cavazos, Javier
Heteroscedastic data analysis
(co-advised with Laura Balzano, ECE)
2021 Rackam Merit Fellow
Wang, Guanhua
MRI with machine learning methods
(co-chaired with Doug Noll, BME)
Xiang, Haowei
MRI
(co-chaired with Doug Noll, BME)
Xu, Alec
Union of subspaces models for heteroscedastic data (EECS 599, W22)
Tao Hong
2021-
ASL MRI / optimization / machine learning / compressed sensing
Co-mentored with Prof.
Luis Hernandez
Anastasia Visheratina
2023-
Eric and Wendy Schmidt AI in Science Postdoctoral Fellow
Nanoscience / Materials Science / Machine learning / Computer vision
Co-mentored with Prof.
Nicholas Kotov,
Department of Chemical Engineering
Xu, Xiaojian
2022-
Inverse problems