Summary
Michele Scipioni is a biomedical engineer and PhD-trained imaging scientist with ten years of experience advancing quantitative PET, MRI and PET/MRI through statistical reconstruction, kinetic modeling, and machine learning. Based at Harvard Medical School/Massachusetts General Hospital, he develops, implements and validates novel image-processing algorithms that improve diagnostic image quality and generate quantitative maps for clinical research. He combines strong programming skills in Python, Matlab, C and CUDA with probabilistic modeling and computer vision expertise, and is a published author active in open-source projects. A committed educator and collaborator, Michele has tutored students and held academic posts while translating research into stakeholder-ready results. Pragmatic and curious, he brings both hands-on algorithm development and a track record of communicating complex methods to diverse audiences.
10 years of coding experience
2 years of employment as a software developer
High school graduation Scientific high school, High school graduation Scientific high school at Liceo Scientifico G. Galilei - Macerata
Bachelor's degree Biomedical/Medical Engineering, Bachelor's degree Biomedical/Medical Engineering at Università Politecnica delle Marche
Master's degree Biomedical/Medical Engineering, Master's degree Biomedical/Medical Engineering at Università di Pisa
Italian, English, Spanish