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Alireza Aghasi
Researcher at Georgia State University
Publications - 55
Citations - 796
Alireza Aghasi is an academic researcher from Georgia State University. The author has contributed to research in topics: Inverse problem & Convex optimization. The author has an hindex of 13, co-authored 48 publications receiving 678 citations. Previous affiliations of Alireza Aghasi include Tufts University & Amirkabir University of Technology.
Papers
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Proceedings Article
Net-Trim: Convex Pruning of Deep Neural Networks with Performance Guarantee
TL;DR: The Net-Trim algorithm prunes (sparsifies) a trained network layer-wise, removing connections at each layer by solving a convex optimization program, and provides a mathematical analysis of the consistency between the initial network and the retrained model.
Journal ArticleDOI
Parametric Level Set Methods for Inverse Problems
TL;DR: In this paper, a parametric level set method for reconstruction of obstacles in general inverse problems is considered, where the level set function is parameterized in terms of adaptive compactly supported radial basis functions.
Journal ArticleDOI
Parametric Level Set Methods for Inverse Problems
TL;DR: In this article, a parametric level set method for reconstruction of obstacles in general inverse problems is considered, where the level set function is parameterized in terms of adaptive compactly supported radial basis functions, which provides flexibility in presenting a larger class of shapes with fewer terms.
Journal Article
Terahertz time-gated spectral imaging for content extraction through layered structures
Alireza Aghasi,Justin Romberg,Albert Redo-Sanchez,Barmak Heshmat Dehkordi,Salman Naqvi,Mingjie Zhang,Ramesh Raskar +6 more
TL;DR: The sub-picosecond time resolution along with spectral resolution provided by terahertz time-domain spectroscopy is exploited to computationally extract occluding content from layers whose thicknesses are wavelength comparable.
Journal ArticleDOI
A Geometric Approach to Joint Inversion with Applications to Contaminant Source Zone Characterization
Alireza Aghasi,Alireza Aghasi,Itza Mendoza-Sanchez,Eric L. Miller,C. Andrew Ramsburg,Linda M. Abriola +5 more
TL;DR: In this paper, a joint inversion approach to shape-based inverse problems was proposed to characterize subsurface contaminant source-zones by processing down gradient hydrological data and cross-gradient electrical resistance tomography (ERT) observations.