PhD in Electrical and Computer Engineering - Signal and Image Processing and Machine Learning (Signal Processing for Sensing and Sensor Networks) in Ann Arbor United States | University of Michigan Ann Arbor

Signal processing is a vast engineering field focused on retrieving, modifying, and preserving data contained within intricate signals and visual data. Techniques in this domain encompass: information compression, analog-to-digital transformation, signal and image recovery/enhancement, adaptive filtering, decentralized sensing and processing, and automated pattern recognition. From the initial development of the fast Fourier transform (FFT) to modern widespread MP3/JPEG/MPEG compression standards, signal processing has powered numerous innovations that enhance daily life. Applications span: medical imaging systems (cardiac scan algorithms and multi-modal image alignment), digital audio technology (MP3 players and noise-reducing headphones), navigation systems (GPS and location-enabled mobile devices), smart vehicle sensors (airbag triggers and crash detection systems), multimedia gadgets (PDAs and smartphones), and digital forensics (online surveillance and voice recognition systems). The University of Michigan approaches signal processing as a scientific discipline where novel techniques are mathematically developed and applied using core theories that enable forecasting of performance boundaries and reliability. UM's signal processing research is pioneering innovative models, methodologies, and technologies that will further influence medical diagnostics and treatments, radar imaging, sensor networks, visual data compression, communication systems, and other critical fields.