Mumin Jin Sass
Mumin Jin Sass is a PhD candidate in electrical engineering and computer science whose research integrates signal processing, machine learning, and array processing to expand the capabilities of sensing systems for radio frequency, acoustic, and other modalities. Supported by her first MathWorks Fellowship, Mumin concentrated on machine-learning approaches to enhance automotive radar imaging in autonomous vehicles. Her second MathWorks Fellowship will enable her to explore a related line of inquiry at the intersection of signal processing and systems and circuits: rethinking analog-to-digital conversion. She aims to create application-specific data converter architectures that leverage the availability of abundant and inexpensive digital signal processing to dramatically reduce the number of bits required to achieve target performance levels. This architecture could enable strongly interference-resistant data conversion. MATLAB has been a critical resource in Mumin’s research, and she has created multiple tools of value for the broader MathWorks community. By developing new approaches to forming high-quality representations of signals with few measurements, Mumin’s work has the potential to advance a wide range of applications, from automotive radars to medical imaging.