Tao Hong
Postdoctoral Fellow at Oden Institute - University of Texas at Austin
Austin, Texas, United States
Summary
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Senior🎓
Top SchoolTao Hong is a postdoctoral fellow at the Oden Institute, bringing nine years of research experience at the intersection of computational imaging, inverse problems, and trustworthy deep learning. His work centers on provable computational methods that make imaging systems—such as photoacoustic tomography and MRI—more reliable and interpretable for biomedical applications. Previously at the University of Michigan and as a visiting student at EPFL, he developed algorithmic foundations for arterial spin labeling and other MRI modalities. Tao blends rigorous theory from his PhD at Technion with practical implementations, aiming to close the gap between mathematical guarantees and real-world imaging pipelines. He maintains an active research portfolio and public presence (hongtao-argmin.github.io) highlighting methods that prioritize provability alongside performance. Colleagues describe him as someone who seeks not just better models, but ones whose behavior can be understood and trusted in clinical contexts.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Technion - Israel Institute of TechnologyVisiting Student, biomedical imaging, Visiting Student, biomedical imaging at EPFL
Github Skills (26)
inverse-problems7
prototyping6
mathematics6
discretization6
imaging6
image-reconstruction6
tomography6
optimization5
iterative5
python5
mri4
operator3
signal-processing3
machine-learning3
signal2
Programming languages (2)
Github contributions (5)
Contributions:25 commits, 3 pushes in 10 months
hongtao-argmin/An-Efficient-Algorithm-Designing-Robust-Projection-Matrix
Apr 2018 - Dec 2022
Contributions:6 commits, 4 pushes, 1 branch in 4 years 8 months
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