SEMINAR S’23-How AI Technology Developed for Deep Space Human Exploration Amplies Humans on Earth Today

• Post by: Bahareh Arghavani
• March 27, 2023
• Comments off

Presenters: Seyed Sajjadi (Founder & CEO nFlux AI, NASA Engineer, Artificial Intelligence Consultant),

Time: Monday 04/17/2023, 3:30 PM – 4:30 pm ET

Place: Maxcy 218
Recording: TBA

Abstract:

Deep space exploration and interplanetary travels are going to require greater amounts of autonomy than current spacecraft systems can support. One of the most important reasons for such a requirement is based on the constrained and delayed communication that distanced spacecrafts are going to have with the flight control room, currently on Earth. This means, the distance between the spacecraft and Earth’s ground control station, would not allow for realt-time or even near-real-time support and thus the crew support technology will have different requirements than the technology currently used in the International Space Station. In this talk, we’ll explore the building blocks of the AI technology that can benefit future deep space crews for interplanetary travels. The proposed agent can potentially serve as a proxy for the human operator on the ground for a variety of purposes including walking astronauts through a task. Reducing the dependence of the spaceship on the flight control room will be a big step towards making deep space travel more feasible. Additionally, we’ll discuss the commercialization path for such technology.

Bio:

Seyed 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 Europa Clipper Systems Engineering team. He contributed to the JPL’s largest application of Model-Based Systems Engineering. Additionally, he contributed to 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.

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 the games. His large-scale frameworks for clustering, recommendation engine 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.

Selected professional highlights:

• Awarded more than $5M contracts from NASA, US Space Force, and US Air Force as principal or co investigator.
• Raised $10M venture funding and capital from top-notch silicon valley and global investors such Amazon, USC, Illuminate, Telefonica and others.
• Published 10+ AI/ML papers in peer-reviewed journals and conferences
• Awarded Forbes 30 Under 30
• Designed, implemented, and tested amazing products and solutions in AI/ML, robotics, and space.
• Built and led world-class teams solving hard problems
• MIT IEEE accepted paper on “Deep structured Learning Approach for Image segmentation”
• American Statistical Association (ASA) “best insight” and “best overall’ awards
• Sigma Xi, The scientific Research Society best research paper award for “applying Machine learning on academic data”
• University of Southern California (USC) most-popular award in California China Startup
• 1st prize of Khwarizmi International award in Robotics
• California Institute of Technology (Caltech) fellowship in Computer Vision