The 9th edition of the Graph Signal Processing (GSP) Workshop will take place from June 8 to 10, 2026, in Madrid as an in-person event, continuing a successful series of workshops held since 2016. This year’s edition is hosted by the Universidad Rey Juan Carlos and co-organised by the ELLIS Unit Madrid and the ELLIS Unit Delft.
The workshop will bring together researchers and practitioners from academia and industry working in the rapidly growing field of graph signal processing (GSP). The goal of GSP is to extend classical signal processing and statistical learning techniques to signals defined on graphs, enabling the analysis of complex structured data arising in modern applications.
The scientific programme will cover both foundational and emerging topics in the field, including graph transforms, sampling theorems, filter design, and the integration of graph signal processing techniques into machine learning frameworks. The workshop will also showcase recent advances at the intersection of graph signal processing and graph machine learning, highlighting the increasing relevance of graph-based approaches within AI research.
Participants will explore a broad range of real-world applications, such as gene expression analysis on biological networks, epidemic spreading over social networks, congestion modelling in telecommunication systems, and the study of brain activity patterns over neural networks. These examples illustrate the versatility of GSP methods in addressing problems involving highly structured and interconnected data.
GSP 2026 will also feature an outstanding lineup of invited speakers from leading international institutions, including Antonio Ortega from the University of Southern California, Daniel P. Palomar from the Hong Kong University of Science and Technology, Gonzalo Mateos from the University of Rochester, Luana Ruiz from the Johns Hopkins University, and Paolo Di Lorenzo from the Sapienza University of Rome. Their participation will provide attendees with a broad overview of current trends and cutting-edge research directions in graph signal processing and graph machine learning.
The paper submissions are officially open until May 15th. The workshop is expected to provide an excellent environment for discussion, collaboration, and the exchange of ideas across the international graph learning and signal processing communities.