Professors Scott Acton and Mathews Jacob of the University of Virginia’s Charles L. Brown Department of Electrical and Computer Engineering were named to the IEEE Signal Processing Society’s 2025 Class of Distinguished Lecturers.
Acton and Jacob are in rare company. The society named only five appointees. Acton and Jacob will serve two-year terms, in 2025 and 2026.
Beyond facilitating access to highly regarded educators and authors in the field, the Signal Processing Society’s Distinguished Lecturer Program also provides financial support for its chapters to host lectures at their meetings.
An Expert in AI for Video Analysis
Acton, the Lawrence R. Quarles Professor and chair of the department, runs the Virginia Image and Video Analysis lab at UVA’s School of Engineering and Applied Science. He also serves as a special adviser to the provost on artificial intelligence. A noted researcher in biomedical image analysis problems, he recently led a project to develop an AI-driven system capable of characterizing human actions in video footage with unprecedented precision and intelligence.
While a potential industry-changer in high-stakes scenarios such as surveillance, healthcare diagnostics or autonomous driving, this technology also underlies a National Science Foundation-supported joint project with UVA’s School of Education and Human Development called Artificial Intelligence for Advancing Instruction.
Its goal is to automate video analysis to help teachers perform better in the classroom.
Acton plans to incorporate this research into a lecture topic. Other topics include learning to use AI rather than fear it, as well as “Using Image Analysis to Unravel Mysteries of the Brain.”
“This is an opportunity for Mathews and me to showcase breakthroughs in signal processing, artificial intelligence and medical imaging, especially those achieved at the University of Virginia,” Acton said.
Making Medical Imaging More Affordable
Jacob also is an expert in developing and applying machine learning algorithms to improve medical imaging. His lab, the Computational Biomedical Imaging Group, recently landed a $3.9 million multi-institute grant to develop technology to detect early signs of Alzheimer’s and dementia. They propose a system that tracks the brain’s metabolic changes using magnetic resonance spectroscopic imaging (MRSI).
Jacob is also leading other National Institutes of Health- and industry-funded efforts in ultrahigh resolution imaging of the brain on 7-Tesla MRI scanners, as well as developing “free-breathing” cardiac MRI that doesn’t require the patient to hold their breath.
“I believe machine learning and signal processing tools can make medical imaging technology significantly more affordable, thereby enhancing healthcare accessibility in the U.S., as well as in developing countries,” Jacob said.
“The Distinguished Lecturer position will enable me to interact with local IEEE SPS chapters, and my hope is to inspire the next generation about the transformative power of signal processing and machine learning in saving lives and shaping the future of healthcare.”
Signal Processing
Signal processing is an electrical and computer engineering subfield focused on generating, manipulating and interpreting signals, whether sound, images or electrical data, to extract useful information. The Signal Processing Society is one of the Institute of Electrical and Electronics Engineers’ oldest professional societies.
Read more about this year’s class of Distinguished Lecturers.