Chris Moberg

Vice President Of Engineering at Ottometric

Chris Moberg has extensive work experience in the technology and engineering fields. Chris is currently the Vice President of Engineering at Ottometric since March 2020. Prior to this, they were the owner and principal calibrator at Viking Performance Tuning from July 2015. In this role, they had in-depth knowledge of automotive systems and was skilled in analyzing and reverse engineering binary ECU files and CAN bus messages.

Before Viking Performance Tuning, Chris worked as a Senior Software Engineer at ACTV from August 2009 to March 2020. Chris'sclients were in the broadcast television market, specifically in real-time sports broadcasting. Chris had expertise in computer vision, including fixed focal length cameras and cameras with pan/tilt/zoom capabilities.

Chris also held positions at Chyron as the Director of Core Technology from August 2008 to July 2009, at Harris Corporation as a Senior Software Engineer from June 2005 to July 2008, and at Leitch Technology as a Software Engineer from March 2003 to June 2005.

Chris Moberg's education history includes studying Computer Engineering at Cornell University. The provided information does not specify the start or end years of this education.

Location

Tampa, United States

Links

Previous companies


Org chart


Teams


Offices

This person is not in any offices


Ottometric

3 followers

Ottometric provides analytics and enhanced capabilities for the automotive supply chain to understand challenges in ADAS features being delivered in modern vehicles. As vehicle complexity increases with more sensors and systems, the complexity and interdependency of the data fusion makes validation ever more complex, time consuming and expensive. The Ottometric solution provides simplified data management and visualization for this overwhelming deluge of validation data and our proprietary artificial intelligence (AI) and computer vision automates validation data review. The result is significant cost reduction and higher accuracy than manual review of data that utilizes in-house tools or unscalable off-the-shelf software. With more extensive and rapid data analysis, long tail problems can be better understood, further improving ADAS features being delivered to the market.


Industries

Employees

11-50

Links