|Adaptive, reliable automation and intelligent decision making are essential for the success of our space ground systems. One big challenge is migrating capabilities out of the lab to supporting critical mission operations. In the past, these approaches were often misunderstood, misapplied, too complex or costly to sustain, or insufficient for mission needs. Applied intelligent systems and machine learning WG technologies have begun to address this challenge through self-evolving, efficient, and value-focused capabilities. In addition, un-realized opportunities exist for applying established, or rapidly emerging technologies, solutions and architectures to the area of ground system space control and mission processing.
This year of the GSAW “Intelligent Systems / Machine Learning for Space Ground Systems” working group will explore deeper the themes of:
- Where do intelligent systems and machine learning currently exist in space ground systems?
- What underlying parts of the space ground systems, enterprise and operations are suited to intelligent systems and machine learning?
- What emerging capabilities and technologies are being developed in the community?
- What are real-world impediments for adoption in operations?
- What capability and technology gaps exist and might seed further research and investment?
|Jon Neff is a data scientist and system engineer in the Civil Systems Group Artificial Intelligence, Analytics and Innovation Department at The Aerospace Corporation. He has worked on development and operations of several NASA robotic space missions and also has experience in software startups and medical devices. Most recently, he was Director, Risk Analytics at Visa. He has a Ph.D. in aerospace engineering from the University of Texas at Austin and an MBA from Pepperdine University.
Dan Balderston is a Senior Engineering Specialist in the Applied Software Technologies Department at The Aerospace Corporation. Dan has many years of experience on Air Force programs in flight software and spacecraft avionics with a focus on anomaly detection, risk assessment and mitigation. In 2018, Dan was part of a team that won an Aerospace Corporation Innovation Award for work on the Watcher satellite cybersecurity application.