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SSPS 2026

Signal processing is an electrical engineering subfield that focuses on analysing, modifying, and synthesizing signals such as sound, images, and scientific measurements. Signal processing techniques can be applied to improve transmission, storage efficiency and subjective quality and to also emphasize or detect components of interest in a measured signal.

Email: adam@asr.org

Machine Learning for Signal Processing: Deep learning/machine learning/AI algorithms; Tools/platforms for AI; Edge and cloud AI computing platforms; Hardware/neuromorphic accelerators; Hardware/software co-design and automation for AI. Design Methods of Signal Processing Systems: Optimization of signal processing algorithms; Compilers and tools for signal processing systems; Algorithm-to-architecture transformation; Dataflow-based design methodologies; Error-tolerant techniques for signal processing. Signal Processing Application Systems: Audio, speech, and language processing; Biomedical signal processing and bioinformatics; Image, video, and multimedia signal processing; Information forensics, security, and cryptography; Sensing and sensor signal processing; Signal processing for non-volatile memory systems; Latency-and power-constrained signal processing; Wireless communications and MIMO systems; Coding and compression; Signal processing for mixed-signal technologies.