Signal, Image and Speech Processing

Signal, Image and Speech Processing spans many applications, including speech recognition, image understanding and forensics, bio-inspired imaging and sensing systems, brain-machine interfaces, and lower power, higher performance communication systems.

New theories and techniques in sparse signal representation and reconstruction, information and game theory applied to data forensics, natural learning, and efficient  processing algorithms enable advances in many different applications.

Signal & Image Recovery: Signal, Image and Speech Processing researchers have uncovered new theories and methods for sparse signal processing, which will enable signal and image recovery with fewer measurements and would otherwise be impossible.

Speech Recognition: Research in Signal, Image and Speech Processing is uncovering the fundamental cues used by humans to recognize speech and developing new speech recognition systems that learn information the way humans do from normal, natural interactions.

Information Forensics: This discipline is finding the limits of information hiding within natural images and methods to detect data doctoring or falsification.

Biological-based Interfaces: New approaches to brain-machine interfaces for paralyzed and novel new sensing systems inspired by biology are in development.

Narendra Ahuja: Next generation cameras, 3D computer vision
Jont Allen: Cochlear modeling, auditory psychophysics
Yoram Bresler: Biomedical imaging systems, inverse problems
Gerald DeJong: Artificial intelligence, automated reasoning
Minh Do: Computational imaging, visual information representation
Mark Hasegawa-Johnson: Acoustic phonetics, audio signal processing
Thomas Huang: Image processing, computer vision
Douglas Jones: Time-varying, time-frequency analysis
Stephen Levinson: Speech processing, language acquisition
Zhi-pei Liang: Magnetic resonance imaging, pattern recognition
Pierre Moulin: Image and video processing,
William O’Brien: Ultrasonic biophysics, bioeffects
Andrew Singer: Statistical signal processing, machine learning