The Rice University DSP group has been conducting research in digital signal processing since 1968. Initially starting in filter design and FFT algorithms, the group has grown substantially over the past three decades, adding researchers working in image and video processing and coding, array processing, wavelets, computational imaging and photography, high-speed digital and analog circuits, and deep learning. A recent expansion has added new capabilities for machine learning and neuroengineering.

DSP group firsts include:

• Parks-McClellan filter design method
• Prime factor and number-theoretic FFT algorithms
• One of the leading wavelet textbooks and the Rice Wavelet Toolbox
• Compressive sensing theory and algorithms
• Single-pixel camera
• FlatCam
• Probabilistic models for deep learning
• Spline theory of deep learning
• Learning analytics for personalized education