Ali Cafer Gurbuz, PhD Home Research Publications Teaching IMPRESS Lab Group
Ali Cafer Gurbuz, PhD

Assistant Professor
Dept. of Electrical and Computer Engineering
Mississippi State University
Email: gurbuz [at] ece [dot] msstate [dot] edu
Phone:
Office: 335 Simrall

CV/Resume
Google Scholar

About Me:

Ali Cafer Gurbuz is an Assistant Professor of Department of Electrical and Computer Engineering at Mississippi State University (MSU). He received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Georgia Institute of Technology, Atlanta, Georgia in 2005 and 2008 respectively.He held post-doctoral, research and faculty positions both in US and Turkey before joining MSU in 2018. He is currently co-director of Information Processing and Sensing (IMPRESS) Lab.

Research Interests:

  • Compressive learning,
  • Deep learning based Inverse Problems and Signal Processing
  • Computational imaging, Sparse Signal Processing, Compressive Sensing
  • Machine Learning for Autonomous Systems, Off-Road Autonomy
  • UAV based Smart Sensing Systems
  • Machine Learning for Radar and Remote Sensing Systems
  • Radar and Array Signal Processing
My lab is looking for to sponsor MULTIPLE Ph.D. students to join our team. Students will be working on cutting edge research in NSF, USDA, Department of Defense funded research projects. Visiting professors/scholars and students are also welcome. Please contact me with your CV, transcripts if you are interested in working in my team.

NEWS

DATE EVENT
February 2021 NSF CAREER Award: I have been awarded NSF CAREER for my project titled "CAREER: Learning to Sense: Joint Learning of Task Oriented Cognitive Sensing with Data Driven Reconstruction and Inference". The project summary can be accessed here
January 2021 Our paper "Robust estimation of the number of coherent radar signal sources using deep learning" is now accepted to IET Radar, Sonar & Navigation
December 2020 Our paper "Attention-Based Domain Adaptation Using Residual Network for Hyperspectral Image Classification" is now published on IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
October 2020 Our paper "Cramer–Rao Lower Bound for SoOp-R-Based Root-Zone Soil Moisture Remote Sensing" is now published on IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
September 2020 New NSF Award: SWIFT: LARGE: AI-Enabled Spectrum Coexistence between Active Communications and Passive Radio Services: Fundamentals, Testbed and Data. Project summary can be accessed here
September 2020 Our paper "American Sign Language Recognition Using RF Sensing" is now available online and can be accessed here on IEEE Sensors Journal
August 2020 Our paper "Joint Learning of Measurement Matrix and Signal Reconstruction via Deep Learning" is now published and can be accessed here on IEEE Transactions on Computational Imaging
June 2020 Our paper "Cognitive Radar Target Detection and Tracking With Multifunctional Reconfigurable Antennas" is now published and available online on IEEE Aerospace and Electronic Systems Magazine
March 2020 Our paper "Joint Learning of Measurement Matrix and Signal Reconstruction via Deep Learning" is now available online on IEEE Transactions on Computational Imaging
March 2020 Our paper "Off-Grid Aware Channel and Covariance Estimation in mmWave Networks" is now available online on IEEE Transactions on Communications
February 2020 Our paper "CRLB based mode selection and enhanced DOA estimation for multifunctional reconfigurable arrays" has been published in Physical Communications. You may access the paper from here