À propos Miguel Tomás Pinto e Silva
Promoting Safe Technology Transformation to Businesses and Individuals
Miguel, a seasoned professional in scientific research and smart technology solutions, adeptly combines hardware and software expertise. With a track record of successful remote team management spanning four years, excel in leading and delivering impactful projects.
Since 2018, Miguel moderated Slack, WhatsApp, and LinkedIn groups, where provided valuable advice and mentorship to individuals and organizations. His LinkedIn, Twitter, and Stack Overflow profiles showcase achievements and contributions.
Noteworthy accomplishments include:
■ Pioneering digital transformation at the University of Minho, Laboratory of Construction and Building Materials from 2005 to 2009.
■ Driving three digital transformations for start-up enterprises between 2007 and 2020.
■ Designed, tested, and prototyped over 70 technology solutions, accessible on GitHub.
■ Specialized in smart self-sensing sensor carbon-based composites for Structural Health Monitoring from 2005 to 2007 and 2017 to 2020-23.
■ Successfully developed a common injection rail prototype for automotive LPG systems in 2014-2016.
Miguel has an extensive portfolio encompassing more than 45 open hardware smart PCB electronics and over 30 open software solutions, available on GitHub repositories: "PCB-Prototyping-Catalogue" and "aeonlabs-open-software-catalogue" respectively.
With five authored and two co-authored scientific journal publications, Miguel possess a deep commitment to advancing knowledge. Miguel holds a Master's degree in Smart Carbon Fiber Composites for Structural Health Monitoring, supplemented by 79.5 ECTS in Master-level courses on Artificial Intelligence and Smart IoT devices from renowned Swedish and Spanish universities for an ongoing 2nd Master Degree.
On his LinkedIn profile, you can find PDF copies of Miguel's university diplomas, course certifications, recommendation letters, and links to published scientific papers. The most recent publication, "A deep neural network for electrical resistance calibration of self-sensing carbon fiber polymer composites compatible with edge computing structural monitoring hardware electronics," is available in the Journal Structural Health Monitoring (doi:10.1177/14759217231170001).
Miguel is eager to leverage his expertise, drive innovation, and contribute to technological advancements.
Thank you for considering me on your search.
For HR and business enquiries send an email to mtpsilva@gmail.com
Since 2018, Miguel moderated Slack, WhatsApp, and LinkedIn groups, where provided valuable advice and mentorship to individuals and organizations. His LinkedIn, Twitter, and Stack Overflow profiles showcase achievements and contributions.
Noteworthy accomplishments include:
■ Pioneering digital transformation at the University of Minho, Laboratory of Construction and Building Materials from 2005 to 2009.
■ Driving three digital transformations for start-up enterprises between 2007 and 2020.
■ Designed, tested, and prototyped over 70 technology solutions, accessible on GitHub.
■ Specialized in smart self-sensing sensor carbon-based composites for Structural Health Monitoring from 2005 to 2007 and 2017 to 2020-23.
■ Successfully developed a common injection rail prototype for automotive LPG systems in 2014-2016.
Miguel has an extensive portfolio encompassing more than 45 open hardware smart PCB electronics and over 30 open software solutions, available on GitHub repositories: "PCB-Prototyping-Catalogue" and "aeonlabs-open-software-catalogue" respectively.
With five authored and two co-authored scientific journal publications, Miguel possess a deep commitment to advancing knowledge. Miguel holds a Master's degree in Smart Carbon Fiber Composites for Structural Health Monitoring, supplemented by 79.5 ECTS in Master-level courses on Artificial Intelligence and Smart IoT devices from renowned Swedish and Spanish universities for an ongoing 2nd Master Degree.
On his LinkedIn profile, you can find PDF copies of Miguel's university diplomas, course certifications, recommendation letters, and links to published scientific papers. The most recent publication, "A deep neural network for electrical resistance calibration of self-sensing carbon fiber polymer composites compatible with edge computing structural monitoring hardware electronics," is available in the Journal Structural Health Monitoring (doi:10.1177/14759217231170001).
Miguel is eager to leverage his expertise, drive innovation, and contribute to technological advancements.
Thank you for considering me on your search.
For HR and business enquiries send an email to mtpsilva@gmail.com
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