John Abraham

John Abraham has a diverse and extensive work experience spanning various roles and industries. John is currently working as the Infrastructure Security Lead at Polygon Labs since 2022. Prior to that, they worked at Freestyle Studios as a Mobile App Developer, where they utilized technologies such as Swift, Java, and React Native for app development. John also worked on projects involving Bluetooth LE and Classic APIs, Python for REST API creation, and Google APIs.

From 2016 to 2021, John was employed at Tygart Technology, Inc., where they held two roles. As the Leader of the AI and Machine Learning Lab, they worked on creating AI/ML capabilities for government and commercial clients, specializing in image classification and detection. Additionally, they were the Tech and Business Lead for the Private Sector, responsible for bringing Tygart's face recognition technology to enterprise opportunities.

Prior to that, John founded EarthPing in 2015, serving as the CTO and Founder. EarthPing focused on producing targeted business intelligence derived from RF signals such as Bluetooth and Wi-Fi. John also founded Redspin in 2001, a successful enterprise security assessment company that was acquired in 2015.

In their earlier career, John worked at Intuit, InterVU (acquired by Akamai), and Websidestory (acquired by Omniture/Adobe), where they held various roles in software development, network engineering, and program/product management. John also worked at Freestyle Studios as an Interactive CD-ROM developer from 1991 to 1995.

John Abraham attended UC Santa Barbara from 1986 to 1990, where they pursued a Bachelor of Science (BS) degree in Environmental Studies, Remote Sensing Geography, and Physics. John then enrolled at San Diego State University from 1999 to 2001, completing most of their coursework towards a Master of Science (MS) degree in Computer Science. In addition, John has obtained several certifications including "Convolutional Neural Networks in TensorFlow," "Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning," "Neural Networks: CNNs," and "Machine Learning" from reputable institutions such as deeplearning.ai and Stanford University.