معرفی
Rafael Delgado Lopez is a Professor in the Department of Applied Mathematics for Information and Communication Technologies at the School of Telecommunications Engineering, Technical University of Madrid (UPM). He joined UPM as a Profesor Ayudante Doctor in September 2020 and was promoted to Profesor Contratado Doctor in September 2023. His research is primarily focused on theoretical particle physics, with expertise in collider phenomenology, lattice QCD, and effective field theories. He is a member of the Geometría y sus aplicaciones research group and has been part of the ADAI project (PID2021-124473NB-I00) since 2021.
Delgado Lopez's research spans several key areas in theoretical physics. His primary interests include Higgs physics, where he investigates multi-Higgs production processes and the differences between Standard Model Effective Field Theory (SMEFT) and Higgs Effective Field Theory (HEFT). He has made significant contributions to lattice QCD, particularly in studying the static energy in multi-flavor QCD and charm mass effects. His work also extends to graviton scattering, unitarization techniques, and computational physics, where he developed the MaMuPaXS tool for numerical integration of cross sections and contributed to the QuantumFDTD computational framework.
His recent publications demonstrate a focus on cutting-edge topics in particle physics, with particular attention to multi-Higgs production, vector boson scattering, and the search for physics beyond the Standard Model. His work often involves complex computational techniques and collaborations with international research groups including those at INFN-Firenze and TUM.
As an academic supervisor, Delgado Lopez has directed multiple student projects, including bachelor theses on elliptic curves cryptography and image classification via machine learning for medical purposes, as well as a master's thesis on the Quantum Walk Algorithm. He has also been involved in the acquisition, administration, and maintenance of high-performance computing resources for the ADAI project.