Seyed (Mehrzad) Sajjadi is a technologist & entrepreneur with more than 15 years of demonstrated history of working in academia, industry, and government. Before founding nFlux AI as a NASA spin-out, Sajjadi joined NASA Jet Propulsion Laboratory (JPL) as part of the Europa Clipper Systems Engineering team. He contributed to... Read more
Seyed (Mehrzad) Sajjadi is a technologist & entrepreneur with more than 15 years of demonstrated history of working in academia, industry, and government. Before founding nFlux AI as a NASA spin-out, Sajjadi joined NASA Jet Propulsion Laboratory (JPL) as part of the Europa Clipper Systems Engineering team. He contributed to the JPL’s largest application of Model-Based Systems Engineering. Additionally, he contributed to the ongoing development of autonomy functionalities for PUFFER (Pop-Up Flat Folding Explorer Robot), an origami-inspired robot concept that would provide future NASA missions with simple, low-cost access to new high-value extreme terrains. More recently, he has been co-investigator on a multi-million dollar NASA research grant for futuristic artificial intelligence systems.
After his exit from nFlux AI, Sajjadi joined Invisible AI to lead product, where he is shaping the strategy, roadmap, and execution of next-generation visual intelligence platforms for manufacturing. He also serves as Entrepreneur-in-Residence at the Terasaki Institute, spinning out biomedical innovations. In addition, he is an Investment Advisor at Plug and Play, where he supports early-stage investments in AI-driven health and biotech ventures.
Previously, under a U.S. Air Force Office of Scientific Research grant, Sajjadi led an interdisciplinary team of 35 engineering and human factors researchers to build the next generation of robotic search and rescue systems with artificial intelligence. His team designed and architected scalable platforms consisting of rovers and drones capable of detecting humans through visual and auditory sensors, mapping and exploring chaotic environments, and communicating with an operator in a Ground Control Station.
During his years as a Data Scientist at Electronic Arts (EA), Sajjadi architected and deployed machine learning pipelines to better understand and predict player behaviors in games. His large-scale frameworks for clustering, recommendation engines, and lifecycle-based behavioral segmentation are being used on tens of millions of users. Sajjadi has consulted Boeing and General Motors (GM) on autonomous systems with a patent pending on autonomous planes. He was previously a computer vision research fellow at Caltech where he designed and applied deep learning and computational methods to quantify image data coming from biological and biomedical experiments.
Over the past 15 years, Mr. Sajjadi has: