Introduction
Presentations
This link
will direct you to some slide presentations which are used to
introduce the group to starting MSc students.
Signal processing theory includes array signal processing, estimation and detection, sampling theory, graph signal processing, convex optimization, distributed processing, machine learning and tensor analysis. We also cover electromagnetics theory. Regarding high-level system design, we have a specific focus on spiking neural network platforms.
Application areas include audio and acoustics, wireless communication, radio astronomy systems, distributed sensing from space, biomedical signal and image processing (MRI, ultrasound, ECG), and computational platforms for autonomous driving (e.g., radar sensor fusion).
The main goal in our research program is to provide a sound mathematical framework for the analysis and synthesis of problems in the complete trajectory from system application, signal processing model, algorithm design, mapping to a digital hardware architecture or embedded system or VLSI circuit, and finally the design verification.
For autonomous driving, GPS is probably not sufficiently accurate or reliable. The SuperGPS project aims to demonstrate a road-side solution that can achieve cm resolution. Here is a 2020 magazine article about it. The project published a Nature paper in Nov. 2022, which was also covered by IEEE Spectrum.
Radio astronomy is an interesting application area for array signal processing. We developed a new image formation tool called PRIFIRA, inspired by Sparse Bayesian Learning.
This simple piece of plastic makes 3D ultrasound easy: read more
The CAS group participates in four MSc tracks in Electrical Engineering: MSc Telecommunication and Sensing Systems, MSc Signals and Systems, MSc Microelectronics, MSc Computer Engineering. We also take students from MSc Biomedical Engineering.
CAS consists of 9 professors and about 40 researchers.
