The IEEE SPS congratulates the following SPS members who will receive the Society’s prestigious awards during ICASSP 2025 in India.

We are excited to announce that registration for the IEEE International Symposium on Biomedical Imaging (ISBI) 2025 is now open! Join us from April 14-17, 2025, in Houston, TX, USA for the premier forum that brings together researchers and practitioners at the forefront of biomedical imaging science and technology.

The IEEE Signal Processing Society (SPS) announces the 2025 Class of Distinguished Lecturers and Distinguished Industry Speakers for the term of 1 January 2025 to 31 December 2026, which are noted below.

The IEEE Signal Processing Society Kolkata Chapter has been selected as the recipient of the 2024 Chapter of the Year Award!

The Signal Processing Society (SPS) conducts webinars presented by professionals in the field of signal processing and related technologies on an ongoing basis. Webinars are also hosted periodically by SPS Technical Committees, and other network of communities. Visit the Upcoming Events page to see a list of our upcoming webinars and join us! Visit the SPS BLOG for more related content on a regular basis!

The IEEE Signal Processing Society (SPS) has planned to launch the Ambassador Program. This initiative aims to provide a platform for our valuable members to become more involved in the Society.

IEEE Signal Processing Society Vice President-Education Roxana Saint-Nom invites nominations for the position of Chief Editor, Resource Center for a 3-year term starting 1 January 2026. Nominations must be received no later than 9 April 2025.

Dr. Roula Nassif  received the Dipl.-Ing. and M.S. degrees in electrical engineering and industrial control in 2013 from Lebanese University, Beirut, and Compiègne University of Technology, France, respectively, and the Ph.D. degree in electrical and computer engineering in 2016 from the University of Côte d’Azur, Nice, France. 

Electromagnetic inverse scattering problems (ISPs) are crucial in noninvasive imaging but challenging due to nonlinearity and computational costs. This blog explores machine learning-based ISP solvers with physics-guided loss functions, emphasizing the role of near-field priors and multiple-scattering effects. Numerical experiments highlight the advantages and limitations of these approaches.