Signal Processing Seminar

Sensor and Machine Learning at The Arizona State University

Andreas Spanias
Arizona State University - SenSIP

This seminar provides a description of the ASU Sensor Signal and Information Processing (SenSIP) center and its application-driven research projects. The center research activities include algorithm development for extracting information from sensors and IoT systems. More specifically center activities are focused on developing signal processing and machine learning methods for various applications including AI-enabled sensing for automotive, IoT solar energy system monitoring, surveillance systems, health monitoring, and sound systems. The center has several industry members that define and monitor research projects typically for Ph.D. student work. SenSIP has also affiliated faculty working on sensor circuits, flexible sensors, radar, smart cameras, motion estimation, secure sensor networks and other systems.


Andreas Spanias is Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University (ASU). He is also the director of the Sensor Signal and Information Processing (SenSIP) center and the founder of the SenSIP industry consortium (now an NSF I/UCRC site). Member companies of the NSF SenSIP center and industry consortium on sensor information processing include: Intel, National Instruments, LG, NXP, Raytheon, Sprint and several SBIR type companies. He is an IEEE Fellow and he recently received the IEEE Phoenix Section Award for Patents and Innovation. He also received the IEEE Region 6 section award (across 12 states) for education and research in signal processing. He is author of more than 300 papers,15 patents, two text books and several lecture monographs. He served as Distinguished lecturer for the IEEE Signal processing society in 2004.

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Overview of Signal Processing Seminar