Miguel á. Ribot

Miguel á. Ribot

Senior Gnss Systems Engineer @ Skydio

About Miguel á. Ribot

Miguel á. Ribot is a Senior GNSS Systems Engineer currently working at Skydio in San Mateo, California. He has a diverse background in GNSS receiver design, radar technology, and signal processing, with previous roles at companies such as ALBORA, oneNav, and Indra.

Current Role at Skydio

Miguel á. Ribot serves as a Senior GNSS Systems Engineer at Skydio, a position he has held since 2022. In this role, he focuses on the design and implementation of GNSS receiver systems, contributing to advancements in satellite-based navigation technologies. His work is integral to the development of Skydio's innovative drone solutions.

Previous Experience at ALBORA

Before joining Skydio, Miguel worked at ALBORA as Co-head of GNSS from 2020 to 2021. During his tenure in Barcelona, he was responsible for overseeing GNSS projects and contributed to the company's research and development efforts in satellite navigation systems. He previously held the position of GNSS R&D Engineer at ALBORA from 2018 to 2020.

Education and Expertise

Miguel holds a Doctor of Philosophy (PhD) in Microsystems and Microelectronics from EPFL, obtained between 2013 and 2017. He also earned a Master of Science (MSc) in Information and Communications Technologies with a specialization in Signal Processing from Universitat Politècnica de Catalunya from 2009 to 2011. His educational background is complemented by a degree in Telecomunicación with a focus on Telemática from Universitat de les Illes Balears, achieved from 2003 to 2008.

Professional Background

Miguel has a diverse professional background in engineering and systems design. He has worked at oneNav, Inc. as a Senior GNSS Systems Engineer from 2021 to 2022, and previously at Indra as a Systems Engineer from 2011 to 2012. His early career included an internship at Ernst & Young and a role as a Radio Access Network Engineer at Ericsson in 2011.

Research and Personal Interests

Outside of his professional roles, Miguel engages in machine learning and quantitative analysis as personal interests. His research experience includes a five-year stint as a Research Assistant at EPFL, where he contributed to various projects in the field of microelectronics and signal processing. His expertise also encompasses statistical signal processing, which is essential for analyzing data in navigation systems.

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