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IMPRESS Lab — Information Processing and Sensing, NC State University Electrical and Computer Engineering

At the Information Processing and Sensing (IMPRESS) Lab, our research lies at the intersection of signal processing and machine learning, with a strong focus on applications in radar, remote sensing and communications. We pursue both fundamental and applied research, spanning the design, development, and experimental validation of advanced sensing systems to cutting-edge techniques in information processing and machine learning. Our work emphasizes developing learning based techniques with the goal of enabling next-generation intelligent sensing and communication technologies.


Recent News

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Research Interests

  • Compressive learning
  • Deep learning based Inverse Problems and Signal Processing
  • Computational imaging, Sparse Signal Processing, Compressive Sensing
  • Integrated Sensing and Communications (ISAC)
  • Signals of Opportunity Based Sensing and Passive Radars
  • Machine Learning for Autonomous Systems
  • UAV based Smart Sensing Systems
  • Machine Learning for Radar and Remote Sensing Systems
  • Radar and Array Signal Processing

Highlights

U.S. Patent 11,301,672 for radar-based sign language interpretation

U.S. Patent 11,301,672

Radar-based methods and apparatus for communication and interpretation of sign languages

Compressive sensing for subsurface imaging with ground penetrating radar

EURASIP Best Paper Award

Compressive Sensing for Subsurface Imaging Using Ground Penetrating Radar, Signal Processing

Multi-frequency RF sensor network for ASL recognition

IEEE SENSORS Top Paper

ASL Recognition Based on Kinematics Derived from a Multi-Frequency RF Sensor Network — selected as a Top Paper by the Technical Program Committee

SMAP radiometer RFI detection in the time-frequency domain

IGARSS Best Paper Finalist

SMAP Radiometer RFI Prediction with Deep Learning Using Antenna Counts (A. M. Alam)

Md Mehedi Farhad, NASA FINESST awardee

NASA FINESST Award

Future Investigators in NASA Earth and Space Science and Technology fellowship (M. M. Farhad)

Join Us — We Are Recruiting!

We are always looking for motivated Ph.D. students and postdoctoral researchers in signal processing, machine learning, radar, and remote sensing. Openings and application details are on our Join Us page.