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Score-Based Diffusion Models for Accelerated MRI Reconstruction — VP-SDE with data consistency achieving SSIM 0.942 at 4x acceleration on fastMRI

Sparse phase unwrapping of InSAR interferograms

MRI reconstruction (e.g., QSM) using deep learning methods

MATLAB implementation of Orthogonal Matching Pursuit to find the sparsest solution to a linear system of equations, via combinatorial search.

Latent Acoustic Mapping (LAM) for Direction of Arrival Estimation

BART: Toolbox for Computational Magnetic Resonance Imaging

Variationally Reweighted Least Squares

From-scratch DSP implementations investigating FFT optimization, compressed sensing, and spectral analysis. Achieves 8x speedup and <5% reconstruction error with comprehensive testing.

A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.

Research homepage

This page features a series of Advanced Matrix Factorization and Decomposition.

Privacy-Preserving Statistical Analysis of Genomic Data using Compressive Mechanism with Haar Wavelet Transform

Construction of Binary/Bipolar Compressed Sensing matrices using BCH codes

Utilities for seed-independent multidimensional nonuniform sampling

The project involves developing a Python library for ECG compressed sensing. The software will include modules for data reading, visualization, compressed-sensing, reconstruction, and evaluation.

Scalable Estimation Architecture for Integrated Sensing and Communication - PLAIN

Public dataset and analysis scripts from the manuscript "Machine Learning-Driven Analytical Models for Threshold Displacement Energy Prediction in Materials." Includes data for monoatomic and polyatomic materials, metadata, and example workflows for analysis and visualization.

Code to reproduce the results from the thesis: "Compressed Sensing - Theoretical Foundations & Application in Magnetic Resonance Imaging"

Source code of the Paper "Sparse Bayesian Generative Modeling for Compressive Sensing" (NeurIPS 24)