Current students:
PhD students
- Brendan Eder: Fall 2025, BME Rotation
- 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
- Kevin Huang: 2022-, Ph.D. candidate in Bioengineering at UIUC: Advance Image Reconstruction in Transcranial Photoacoustic Computed Tomography (main advisor: Dr. Anastasio)
- Refik Cam: 2022-, Ph.D. candidate in Electrical and Computer Engineering at UIUC: Dynamic Imaging using Photoacoustic Tomography (main advisor: Dr. Anastasio)
- Gangwon Jeong: 2022-, Ph.D. candidate in Bioengineering at UIUC: Accurate Breast Imaging in Photoacoustic Computed Tomography Enabled by Acoustic Property Estimation in Heterogeneous Media(main advisor: Dr. Anastasio)
Past students
The University of Texas at Austin:
- Luke Lozenski: 2025, Ph.D. in System Science and Mathematics at WashU: Model-based and learning image reconstruction methods for photoacoustic tomography. Now postdoctoral researcher at DTU Compute
- Jenil Shah: 2025, MS in Computational Science, Engineering, and Mathematics (CSEM): Low Rank-Based Image Reconstruction Methods for Dynamic Contrast Enhanced Multispectral Optoacoustic Tomography. Now finantial analyst.
- Thomas Wynn: 2025 Undergraduate Research Assistant. Now Fullbright fellow at the Neuro-X Institute of the
Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
- Fu Li: 2024, Ph.D. candidate in Bioengineering at UIUC: Ultrasound Computed Tomography (main advisor: Dr. Anastasio). Now Software Engineer at Pony AI
- Venugopal Ranganathan: 2024 Solving Large-Scale Inverse Problems in hIPPYlibX: An Application to Quantitative Photoacoustic Tomography, MS in Computational Science Engineering & Mathematics (CSEM) (co-advised with Dr. Ghattas). Now Ph.D. student in at UT Austin.
- Karan Prakash Hiranandani: 2023 hIPPYfire: an inexact Newton-CG method for solving inverse problems governed by PDE forward models, MS in Computational Science Engineering & Mathematics (CSEM) (co-advised with Dr. Ghattas). Now R&D Engineer at ANSI
- 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
Washington University in St Louis
- 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