Mr. Emanuele Buchicchio | Instrumentation | Best Researcher Award

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..

Professional Profiles:

• Orcid Profile
• ResearchGate Profile
• LinkedIn

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)

 

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

 

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