Dror Baron

Biography
Prof. Baron's undergraduate studies were in the Electrical Engineering Department at the Technion - Israel Institute of Technology, where he belonged to the Technion's Program for Outstanding Students. Following his graduation, he designed hardware modems at Witcom, an Israeli startup specializing in broadband wireless communication. At the same time he was pursuing his MSc, also at the Technion. In 1999 he joined the Department of Electrical and Computer Engineering and the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign, where he completed his PhD in 2003. During the Spring 2003 semester, he was a Visiting Assistant professor at the University of Illinois.
After completing his PhD, Prof. Baron was a Postdoctoral Research Associateiate in the Department of Electrical and Computer Engineering at Rice University from 2003 to 2006, where he performed research with the Digital Signal Processing research group, which was among the pioneering groups in compressed sensing. From 2007 to 2008 he was a Quantitative Research Analyst with Menta Capital in San Francisco, where he developed quantitative investment strategies. After spending 2008 to 2010 as a Visiting Scientist in the Electrical Engineering Department at the Technion, Prof. Baron joined NC State in 2010 as an Assistant Professor.
Generally speaking, Prof. Baron's research lies on the intersection of fast algorithms, signal processing, and information theory. He is particularly interested in developing systems that extract as much information as possible from data in a computationally timely manner.
Education
-
Ph.D.
2003
Electrical Engineering
University of Illinois at Urbana-Champaign -
Master's
1999
Electrical Engineering
Israel Institute of Technology, Haifa -
Bachelor's
1997
Electrical Engineering
Israel Institute of Technology, Haifa
Research Focus
- Communications and Signal Processing
Funded Research
- High Dimensional Inverse Methods for Electronic System Design, Center for Advanced Electronics Through Machine Learning (CAEML) Core Project
- High-Dimensional Structural Inference for Non-Linear Deep Markov or State Space Time Series Models, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 3A4
- Fast, Accurate PPA Model-Extraction, Center for Advanced Electronics through Machine Learning (CAEML) Core Project 3A2 funded with industry membership dues.
- mm/sub-mm Wave Compressive Sensing Imaging
Awards & Honors
- 2010 - IEEE Senior Member
- 2002 - Honorable mention, Robert Bohrer Memorial Student Workshop, Department of Statistics, University of Illinois
- 2002 - M. E. Van Valkenburg Graduate Research Award, University of Illinoois
- 1994-1997 - Participant in Program for Outstanding Students, Technion
- 1994-1997 - President's Roll every semester, Technion
Recent News

AI Researchers Tackle Longstanding ‘Data Heterogeneity’ Problem for Federated Learning
Posted on July 15, 2022 | Filed Under: News
NC State ECE researchers have developed a new approach to federated learning that allows them to develop accurate artificial intelligence (AI) models more quickly and accurately.

Algorithmic Research Could Reduce Testing Quantities Needed by 85%
Posted on April 10, 2020 | Filed Under: Research
A team led by Dror Baron at NC State ECE is working on a sophisticated algorithm estimated to reduce the number of tests required for group coronavirus testing by up to seven times.

Algorithm Makes Hyperspectral Imaging Faster
Posted on February 18, 2016 | Filed Under: News and Research
Researchers from North Carolina State University and the University of Delaware have developed an algorithm that can quickly and accurately reconstruct hyperspectral images using less data.
Recent Media Mentions

Speeding Up Hyperspectral Imaging
February 25, 2016
A team of researchers from NC State and the University of Delaware have devised a new, faster image-reconstruction algorithm for hyperspectral-image data sets. Dror Baron, engineering, featured.

A Fictional Compression Metric Moves to the Real World
July 28, 2014
Researchers are poised to use the Weissman scores to show efficacy of compression algorithms. Dror Baron, electrical and computer engineering, featured.
Recent Publications
- CONTACT TRACING ENHANCES THE EFFICIENCY OF COVID-19 GROUP TESTING (2021)
- High Speed Receiver Modeling Using Generative Adversarial Networks (2021)
- Local Convergence of an AMP Variant to the LASSO Solution in Finite Dimensions (2021)
- An Approximate Message Passing Framework for Side Information (2019)
- Analysis of Approximate Message Passing With Non-Separable Denoisers and Markov Random Field Priors (2019)
- Performance Limits With Additive Error Metrics in Noisy Multimeasurement Vector Problems (2018)
- An overview of multi-processor approximate message passing (2017)
- Analysis of approximate message passing with a class of non-separable denoisers (2017)
- Conditional approximate message passing with side information (2017)
- Generalized geometric programming for rate allocation in consensus (2017)