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Alessandro Fumarola has a diverse work experience in various companies and research institutions. In 2015, they worked as a Summer Research Intern at NanoLAB - EPFL, where they carried out research on an unspecified project. In 2016, they were a Research Intern at IBM and also started their PhD studies in the H2020 Phase Change Switch Project at Max Planck Institute of Microstructure Physics. At Max Planck, they were later promoted to the role of Guest Scientist, where they advised research projects, performed circuit simulations, and mentored PhD students. In 2017, Alessandro worked as a Visiting PhD Student at EPFL, focusing on the characterization and simulation of radio-frequency devices. In 2021, they joined Mythic as an Analog Compute Modeling Engineer, contributing to the development of Mixed-Signal Accelerators for Machine Learning workloads. Later in 2022, Alessandro joined Electra Vehicles, Inc. as a Data Scientist, where they create predictive algorithms for battery systems. Lastly, in 2020, they worked at Material Mind as a Data Scientist, building data infrastructure and processing pipelines for their Materials Discovery Engine.

Alessandro Fumarola has an extensive education history in the field of engineering and applied physics. Alessandro obtained a Doctor of Philosophy (PhD) degree in Engineering Physics/Applied Physics from The Martin Luther University of Halle-Wittenberg. Prior to this, they completed a Master of Science (M.Sc.) degree in Nanotechnology for the Integrated Systems from both EPFL (École polytechnique fédérale de Lausanne) and Grenoble INP - Phelma. Additionally, they also hold a Master of Science (M.Sc.) degree in Nanotechnology for the Integrated Systems from Politecnico di Torino. Alessandro's educational journey began with a Bachelor of Engineering (B.Eng.) degree in Electrical and Power Engineering from Politecnico di Torino. Furthermore, they have obtained certifications in Confluence Fundamentals and Jira Fundamentals from Atlassian in February 2023.