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Emanuele Ruffaldi has a diverse work experience in the field of software engineering and academia. Emanuele started their career in 2003 as a Visiting Researcher at the University College London. In 2005, they worked as a Visiting Student at Stanford University. From 2007 to 2018, they served as an Assistant Professor at Scuola Superiore Sant'Anna. In 2018, they joined Medical Microinstruments, Inc. as a Senior Software Engineer and later became the Lead Software Engineer. In their role at Medical Microinstruments, Inc., they led the MMI Software team and was responsible for releasing the Symani software on the market, as well as investigating its future. Emanuele also played a key role in shaping requirements, conducting risk analysis, and contributing to system workflow.

Emanuele Ruffaldi has a strong educational background in engineering. Emanuele obtained a Ph.D. in Engineering (Perceptual Robotics) from Scuola Superiore 'Sant' Anna' di Studi Universitari e di Perfezionamento, graduating in 2006. Prior to that, they earned an M.Sc. degree in Engineering from the same institution from 1997 to 2003. Additionally, they pursued another M.Sc. in Engineering from Università di Pisa, completing it between 1997 and 2002.

In terms of certifications, Emanuele Ruffaldi has achieved various accomplishments. Emanuele became a National Academic Qualification as a Full Professor in Computer Engineering in July 2020 from MIUR (Ministry of Education, Universities, and Research). Prior to that, they obtained the National Academic Qualifications as an Associate Professor in Applied Mechanics in November 2018 and as an Associate Professor in Computer Engineering in July 2018, both from MIUR. Furthermore, they have certifications in LabVIEW, including being a Certified LabVIEW Embedded Systems Developer (obtained in February 2022), a Certified LabVIEW Architect (obtained in January 2020), a Certified LabVIEW Developer (obtained in November 2018), and a Certified Associated LabVIEW Developer (CLAD) (obtained in October 2018).

It is worth noting that Emanuele Ruffaldi also completed a Deep Learning Specialization, although the specific institution and date of completion are not provided.