Neurotechnology
Antonello Mincone has a diverse work experience spanning multiple roles and industries. Antonello started their career as an Amiga Demo Coder for companies like Scoopex, Nah-Kolor, and Biosynthetic Design from 1995 to 2000. Antonello then worked as a Lecturer teaching C/Java/ASP/Visual Basic at Infobasic - Istituto di Alta Formazione from 2002 to 2005. After that, they joined Esalab srl as a Web Applications Developer, specializing in full-stack .NET development for enterprise portals from 2004 to 2005.
In 2006, Antonello Mincone joined Neurotechnology and held various positions over the years. Antonello started as an Algorithm Developer, where they developed and implemented methodologies to speed up the fingerprint matching algorithm. In 2008, they became a Sales Manager and focused on optimizing the speed/accuracy trade-off for the company's fingerprint matching algorithm. From 2009 to 2011, Antonello served as a Project and Sales Manager, working on algorithm engineering and marketing strategies for the company's match-on-card technology. Finally, since 2011, they have been a Business Development Manager and Product Manager, responsible for managing long-term relations with key customers and partners worldwide, as well as contributing to the product marketing strategy for automated biometric identification systems.
Overall, Antonello Mincone has a strong background in algorithm development, sales, marketing, and business development across various industries.
Antonello Mincone obtained a Master of Management and Business Administration degree with a focus on International Marketing and Management from the ISM University of Management and Economics in 2009. Prior to that, they completed a Master of Science degree in Electronic Engineering from the Università Politecnica delle Marche in 2004. Antonello Mincone has also obtained a certification in Product Strategy from Kellogg Executive Education in 2022.
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Neurotechnology
Neurotechnology was founded with the key idea of using neural networks for applications such as biometric person identification, computer vision, robotics and artificial intelligence. Much to our delight, we were able to endure the "neural networks winter" by using and expanding this expertise all through 2012, the year that brought explosive developments in the concept and infrastructure of deep neural networks. This allowed us to quickly take advantage of the emerging opportunities that came with the new wave of deep learning and triggered an entire range of new projects in object recognition and other applications. Currently, our team is comprised of more than 100 employees, 15% of whom hold a Ph.D. and half of our employees are actively involved in R&D activities.