Filippo Ranalli, Ph.D.
About Filippo Ranalli, Ph.D.
Filippo Ranalli, Ph.D., is a Data Scientist with expertise in applying artificial intelligence to virtual design and construction projects. He has a diverse background in engineering, having worked in various internships and research roles across multiple locations, including Australia and the United States.
Work at DPR Construction
Filippo Ranalli has been employed at DPR Construction as a Data Scientist since 2021. His role involves leveraging data analytics and artificial intelligence to enhance project outcomes and efficiencies within the construction sector. Based in Amsterdam, North Holland, he contributes to various initiatives aimed at integrating advanced technologies into construction processes.
Education and Expertise
Filippo Ranalli holds a Doctor of Philosophy (PhD) in Optimization and AI in Civil Engineering from Stanford University, which he completed from 2016 to 2021. He also earned a Master of Science (MS) in Structural Engineering from Stanford University between 2014 and 2016, and a Bachelor of Science (BS) in Civil Engineering from Sapienza Università di Roma from 2010 to 2013. His academic background provides a strong foundation in applying artificial intelligence to virtual design and construction (VDC) projects.
Background
Filippo Ranalli began his professional journey as a Marketing Intern at Allplastics Engineering in Sydney, Australia, in 2014. He then gained experience as a Structural Engineering Intern at Rivera Consulting Group, Inc. in San Francisco, CA, in 2015. In 2018, he worked as a Software Engineering Intern at One Concern in Palo Alto, California. Additionally, he served as a Graduate Research and Teaching Assistant at Stanford University School of Engineering from 2016 to 2021.
Research and Development Projects
Filippo Ranalli has been actively involved in research and development projects that focus on the application of artificial intelligence within the construction industry. His work aims to innovate and improve construction methodologies through the integration of advanced technologies, contributing to the evolution of practices in the field.