# Jordan Marr

Location: San Francisco Bay Area, United States
Profile: https://flows.cv/jordanmarr

My key skills are in the use of numerical optimization and machine learning to calibrate sensors and fuse data coming from multiple (potentially noisy) sources. As my Master’s thesis, I’ve developed an algorithm for calibrating a suite of many sensors (automatically discovering their poses relative to each other, so that the data can be fused to a consistent coordinate frame). This allows the system to perform a number of tasks such as scanning and building a point cloud of an object or a room or, if you attach it to a mobile platform, autonomous navigation. 

I also have a strong background in C++ and CUDA development from my work at NVIDIA in the Autonomous Vehicles group. This has given me an appreciation for software development fundamentals such as robust CI/CD pipelines, and using all available tools to enhance reliability and portability. Some of the specific technologies I use are Python for internal tool development, GTest for CI test development, OpenGL for GUI applications, and Docker for ensuring portability.

My philosophy is that life-long learning is the key to success, and as such, I am always looking to push the boundaries of what is possible in my work in both research and industry.

## Education
### Master of Applied Science (MASc) in Robotics
University of Toronto
Jan 2016 – Jan 2018

### Bachelor of Science in Engineering (BScE) in Electrical Engineering
Queen's University
Jan 2012 – Jan 2016


## Contact & Social
- LinkedIn: https://linkedin.com/in/jordan-marr-1a543185
- Website: https://jdmarr-homepage.herokuapp.com/
- Website: https://github.com/jdmarr

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Source: https://flows.cv/jordanmarr
JSON Resume: https://flows.cv/jordanmarr/resume.json
Last updated: 2026-04-05