David García-Azorín is currently affiliated with the Hospital Clínico Universitario de Valladolid. He obtained his medical degree at the Universidad Complutense de Madrid. He completed his residency in neurology at the Hospital Clínico Universitario de Madrid. He completed his specialization in headache during a clinical fellowship at the Hospital Clínico Universitario in Valladolid and the Master of Headache Disorders at the University of Copenhagen, Denmark. He completed his training in clinical research through the program Principles and Practice of Clinical Research at Harvard Medical School and a Master's Program in Clinical Research at Dresden International University, Germany. He completed his Ph.D. in the detection of secondary headaches in the emergency department at the University of Valladolid. He is currently a member of the Spanish Society of Neurology executive board, chair of the International Area, and secretary of the UEMS (European Board of Neurology). He is involved in the European Academy of
Neurology in the headache panel and neuroinfectious diseases panel. He recently participated in the elaboration of the WHO guidelines for the management of thrombosis with thrombocytopenia syndrome. His main areas of interest are secondary headache detection and characterization, phenotypic characterization of other primary headache disorders, and current headaches attributed to COVID-19.
Álvaro Planchuelo-Gómez received his PhD in Telecommunications and Information Technology Engineering (specialization in Biomedical Engineering) at the University of Valladolid, Spain, in June 2021. He is a postdoctoral researcher at the Imaging Processing Laboratory, University of Valladolid, Spain, after ending a 2-year postdoctoral stay at CUBRIC (Cardiff University Brain Research Imaging Centre), Cardiff, United Kingdom, in February 2024, and is supported by the NextGenerationEU (European Union) program for three years (2022-2024). His main research is focused on the development of diffusion MRI pre- and post-processing pipelines applied to ultra-low-field diffusion MRI data and the optimization of diffusion–relaxation MRI acquisition sequences via deep learning and physical modeling. Further research is focused on the statistical analysis of MRI-based descriptors to assess structural brain properties in clinical groups, specifically episodic and chronic migraines, and COVID-19 persistent headaches.