Marco D. Santambrogio

Politecnico di Milano, Massachusetts Institute of Technology

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About

Marco D. Santambrogio is a leading figure in reconfigurable computing, with a research focus on efficiently bridging the gap between high-level algorithms and hardware acceleration. His major contributions lie in the design automation of deep learning and image processing on Field Programmable Gate Arrays (FPGAs). He pioneered practical implementations of Convolutional Neural Networks (CNNs) on reconfigurable architectures, with his 2016 work on hardware design automation serving as a foundational reference. Santambrogio’s impact is demonstrated through his highly cited work on the PYNQ platform (29 citations), which showed how to efficiently deploy deep learning algorithms on FPGA-based systems, making them accessible for broader applications. He also advanced mobile robotics through dynamic reconfiguration techniques (23 citations), enabling highly customizable color recognition modules. His recent work, Hephaestus (2023), pushes the boundaries of medical imaging by codesigning and automating 3D image registration on reconfigurable hardware, addressing a critical need in healthcare. With a career spanning over a decade, Santambrogio’s research consistently emphasizes practical, automated solutions that make reconfigurable computing a viable tool for modern, data-intensive challenges.