| Jordan Noone | |
| Birth Date: | 30 November 1992 |
| Birth Place: | Pasadena, CA |
| Education: | University of Southern California (BS) |
| Employer: | Relativity Space, Embedded Ventures |
| Co-Founder, Founding CTO, and Executive Advisor of Relativity Space General Partner, Embedded Ventures | |
Jordan Noone (born 1992) is an American aerospace engineer and the Founding CTO of Relativity Space. He is now a General Partner at Embedded Ventures[1] which he co-founded in 2020 with Jenna Bryant.[2]
Noone became the first student and youngest individual in the world to get Federal Aviation Administration clearance to fly a rocket to space while leading the Rocket Propulsion Lab at the University of Southern California.[3]
See main article: Blue Origin. In 2013, after his junior year at the University of Southern California, Noone interned with Blue Origin's propulsion group.[4]
After graduating from the University of Southern California, Noone was hired by SpaceX as an In-Space Propulsion Development Engineer.[5]
See main article: Relativity Space. Noone co-founded Relativity Space, a company building a 3D printer for rockets, with Tim Ellis in 2015. As of October 2019, the company had raised $185 million in equity and grew to over 170 employees.[6]
In September 2020, Noone stepped down as the CTO of Relativity Space, becoming an Executive Advisor to the company.[7]
Noone is listed as the inventor on two of Relativity Space's patents: "Real-time adaptive control of additive manufacturing processes using machine learning" and "Real-time adaptive control of manufacturing processes using machine learning."
Noone was recognized by Forbes in two of their 30 Under 30 lists in 2019 - the Manufacturing and Industry list[8] and the Big Money list.[9]
In 2018, Noone was included on Inc.'s Rising Stars list of Most Inspiring Young Entrepreneurs.[10]
Business Insider recognized Noone on their 2018 "30 And Under: These are the rising stars in tech who are driving innovation" list.[11]
Noone currently holds two patents for real-time adaptive control of manufacturing processes using machine learning,[12] and is skilled at Matlab and Simulink.[13]