2026 Justin Romberg: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	49	5730	5567	2601	2510	238	45212

Research.com Recognitions

2021 - Jack S. Kilby Signal Processing Medal For groundbreaking contributions to compressed sensing.
2018 - IEEE Fellow For contributions to compressive sensing

Overview

Justin Romberg is affiliated with the Georgia Institute of Technology in the United States. Their research spans multiple fields including computer science and engineering, with a specific focus on subfields such as artificial intelligence, computer networks and communications, computational mechanics, electrical and electronic engineering, and signal processing.

The scientist has a significant body of work centered around topics including:

Sparse and compressive sensing techniques
Distributed control multi-agent systems
Stochastic gradient optimization techniques
Reinforcement learning in robotics
Underwater acoustics research
Advanced bandit algorithms research
Adaptive dynamic programming control

Justin Romberg has published extensively, with numerous papers appearing in key venues. Frequent publication venues include:

arXiv (Cornell University)
The Journal of the Acoustical Society of America
IEEE Transactions on Automatic Control
SIAM Journal on Mathematics of Data Science
IEEE Transactions on Circuits and Systems I Regular Papers

Recent papers authored or coauthored by Romberg include:

STAN: spatio-temporal attention network for pandemic prediction using real-world evidence, 2020, Journal of the American Medical Informatics Association
Convergence Rates of Distributed Gradient Methods Under Random Quantization: A Stochastic Approximation Approach, 2020, IEEE Transactions on Automatic Control
Finite-Sample Analysis of Two-Time-Scale Natural Actor-Critic Algorithm, 2022, IEEE Transactions on Automatic Control
Finite-Time Performance of Distributed Temporal-Difference Learning with Linear Function Approximation, 2021, SIAM Journal on Mathematics of Data Science
A Hardware-Friendly Approach Towards Sparse Neural Networks Based on LFSR-Generated Pseudo-Random Sequences, 2020, IEEE Transactions on Circuits and Systems I Regular Papers

Their frequent collaborators include:

Thinh T. Doan
Mark A. Davenport
Saibal Mukhopadhyay
Coleman DeLude
Sihan Zeng

Justin Romberg has received notable awards including the Jack S. Kilby Signal Processing Medal in 2021 for contributions related to compressed sensing, and they were named an IEEE Fellow in 2018 for contributions to compressive sensing.

Best Publications

Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

E.J. Candes;J. Romberg;T. Tao

20135
Citations
Stable signal recovery from incomplete and inaccurate measurements

Emmanuel J. Candès;Justin K. Romberg;Terence Tao

9142
Citations
Sparsity and incoherence in compressive sampling

Emmanuel Candès;Justin Romberg

2781
Citations
Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

J.A. Tropp;J.N. Laska;M.F. Duarte;J.K. Romberg

1397
Citations
Imaging via Compressive Sampling

J. Romberg

1345
Citations
Bayesian tree-structured image modeling using wavelet-domain hidden Markov models

J.K. Romberg;Hyeokho Choi;R.G. Baraniuk

807
Citations
Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions

Emmanuel J. Candes;Justin Romberg

742
Citations
Signal recovery from random projections

Emmanuel J. Candes;Justin K. Romberg

712
Citations
Compressive Sensing by Random Convolution

Justin Romberg

678
Citations
An Overview of Low-Rank Matrix Recovery From Incomplete Observations

Mark A. Davenport;Justin Romberg

472
Citations
Blind Deconvolution Using Convex Programming

Ali Ahmed;Benjamin Recht;Justin Romberg

469
Citations
Practical Signal Recovery from Random Projections

Justin Romberg

452
Citations
Restricted isometries for partial random circulant matrices

Holger Rauhut;Justin K. Romberg;Joel A. Tropp

242
Citations
Compressive Sensing on a CMOS Separable-Transform Image Sensor

Ryan Robucci;Jordan D Gray;Leung Kin Chiu;Justin Romberg

231
Citations
Terahertz time-gated spectral imaging for content extraction through layered structures.

Albert Redo-Sanchez;Barmak Heshmat;Alireza Aghasi;Salman Naqvi

223
Citations
Compressive sensing on a CMOS separable transform image sensor

R. Robucci;Leung Kin Chiu;J. Gray;J. Romberg

222
Citations
A Nonuniform Sampler for Wideband Spectrally-Sparse Environments

M. Wakin;S. Becker;E. Nakamura;M. Grant

186
Citations
Sparse Recovery of Streaming Signals Using $ll_1$ -Homotopy

M. Salman Asif;Justin K. Romberg

183
Citations
Dynamic Updating for $ll_{1}$ Minimization

M. Salman Asif;J. Romberg

159
Citations
Hidden Markov tree modeling of complex wavelet transforms

Hyeokho Choi;J. Romberg;R. Baraniuk;N. Kingsbury

158
Citations

Frequent Co-Authors

Mark A. Davenport Georgia Institute of Technology

Arijit Raychowdhury Georgia Institute of Technology

Emmanuel J. Candès Stanford University

Michael B. Wakin Colorado School of Mines

Joel A. Tropp California Institute of Technology

Ramesh Raskar MIT

Richard G. Baraniuk Rice University

Magnus Egerstedt University of North Carolina at Chapel Hill

Hua Wang Georgia Institute of Technology

Cao Xiao General Electric (United Kingdom)

External Links

Personal website of Justin Romberg

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