šØāš«Emanuele Buchicchio – Short Biography Emanuele Buchicchio, an Italian software engineer and dedicated Ph.D. student, resides in Todi, Italy. With a profound passion for science and technology, Emanuele has amassed extensive experience in diverse software projects and products. His expertise spans web application design, .Net, C#, Java, machine learning, cybersecurity, and more. Holding positions of Chief Technology Officer and Chief Information Security Officer at Smartpeg, he spearheads AI-powered solutions for human resource management. Emanuele is currently pursuing a Ph.D. at the University of Perugia, focusing on artificial intelligence, machine learning, and measurement tools. His multifaceted skills encompass industrial IoT, embedded systems, and cloud computing.. š
š Professional Profiles:
š Education
Ph.D. Winter/Summer Schools (2020-2022) Machine Learning Engineer with Microsoft Azure Nanodegree (Oct. 2020 – Jan. 2021) Master of Business Administration (MBA, 2011) MEng Computer Engineering (2006) BS Information Technology Engineering (2004)
š key Skills
Web application design and development .Net, .Net Core, C#, Java, JavaEE, Typescript, Angular, Python Industrial IoT, Embedded Systems, Measurements, and data acquisition Machine learning, deep learning, cybersecurity ISO 27001, Cloud (Microsoft Azure, Google Cloud), Agile software development GDPR compliance
š©āš¼ Work Experience
Ph.D. Student (Since Nov. 2020): University of Perugia – Instrumentation & Measurement Chief Technology Officer (Since July 2016): Smartpeg srl, Perugia Senior Software Developer (June 2014 – July 2016): Pegaso200 srl, Corciano Consultant / Software Developer (Feb. 2011 – Jun. 2014): Gianos Consulting S.r.l., Orvieto Product Manager (Oct. 2008 – Jan. 2011): Eles Semiconductor Equipment, Todi Software Engineer (Jan. 2007 – Oct. 2008): Eles Semiconductor Equipment, Todi
Research Focus:
Emanuele Buchicchio’s research revolves around innovative applications in instrumentation, measurement, and artificial intelligence, contributing significantly to battery technology and beyond. His work spans diverse areas such as: Battery Systems: Specializing in Electrochemical Impedance Spectroscopy (EIS), Emanuele explores uncertainty characterization and state-of-charge estimation. His contributions to battery SOC estimation using machine learning and equivalent circuit models are noteworthy. Gesture Recognition: Emanuele delves into novel realms with a magnetic positioning system, employing Convolutional Neural Networks (CNNs) for accurate gesture recognition in sign language, showcasing the