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- Evan Craft Scope: 2023-, Ph.D. candidate in Computational Science, Engineering, and Mathematics (CSEM) at UT Austin: Optimal experimental design of Photoacoustic tomography imaging systems
- Luke Lozenski: 2020-, Ph.D. candidate in System Science and Mathematics at WashU: Model-based and learning image reconstruction methods for photoacoustic tomography
- Fu Li: 2019-, Ph.D. candidate in Bioengineering at UIUC: Ultrasound Computed Tomography (main advisor: Dr. Anastasio)
- Kevin Huang: 2022-, Ph.D. candidate in Bioengineering at UIUC: Model-based and learning-based image reconstruction methods for transcranial photoacoustic computed tomography (main advisor: Dr. Anastasio)
- Refik Cam: 2022-, Ph.D. student in Electrical and Computer Engineering at UIUC: Dynamic Imaging usig Photoacoustic Tomography (main advisor: Dr. Anastasio)
- Thomas Wynn
- Venugopal Ranganathan (co-advised with Dr. Ghattas): Solving Large-Scale Inverse Problems in hIPPYlibX: An Application to Quantitative Photoacoustic Tomography, MS in Computational Science Engineering & Mathematics (CSEM), 2024
- Karan Prakash Hiranandani (co-advised with Dr. Ghattas): hIPPYfire: an inexact Newton-CG method for solving inverse problems governed by PDE forward models, MS in Computational Science Engineering & Mathematics (CSEM), 2023
- Saleh, Bassel (co-advised by Dr. Ghattas): Scientific Machine Learning A Neural Network-Based Estimator for Forward Uncertainty Quantification, BS in Computer Science, Turing Scholars Honors, 2018
- Di Liu (co-advised by Dr. Ghattas): hIPPYLearn: an inexact Stochastic Newton-CG method for training neural networks, MS in Computational Science Engineering & Mathematics (CSEM), 2017
- Ge Gao (co-advised by Dr. Ghattas): hIPPYLearn: an inexact Newton-CG method for training neural networks with analysis of the Hessian, MS in Computational Science Engineering & Mathematics (CSEM), 2017
- Peijie Qiu (Master thesis 2020--2021): Data-Driven Approaches to Solve Inverse Problems
- Jieqiong Xiao (Master Research, SPRING 2019): ADLA: Automatic differentiation and local assembly of exotic finite element variational forms in MFEM
- Argho Dattas (Undergraduate research, Fall 2018): Proximal Newton-type Methods
- Tao Ge (Graduate rotation, Fall 2018): Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization