Leonardo Suriano

Leonardo Suriano is a Ph.D. student at the Universidad Politécnica de Madrid (UPM), affiliated with the Department of Electronic Engineering. His research focuses on runtime adaptive hardware/software execution in complex heterogeneous systems (CPU + FPGA + GPU), high-performance computing, parallel computing, and embedded systems. He has contributed to European projects Enable S3 and Cerbero, developed tools for dataflow-based design space exploration, and is a contributor to the PREESM open-source project on GitHub.

His work bridges hardware acceleration, cyber-physical systems, and real-time computation. He received the

• Best Research Project at the Industrial Research Meeting 2016
• Best Oral Session award in the Simposio Tu Tesi en 4 Minutos (UPM, 2018)

He has published extensively on heterogeneous MPSoC optimization, inverse kinematics, and image processing, with key subfields including GPU/FPGA integration, task scheduling, and firmware development.