Danielle Wood will be speaking as a panel member for Earth Science Sensor Networks at the CTO (Chief Technology Officer) Innovation Summit hosted by the Johns Hopkins Applied Physics Laboratory.
The Earth Science Enterprise sub-theme will center on a scenario based planning discussion related to future climate disaster. Space Based Sensor Network roles explore a complex but “potential” scenario, then layer on complexities that break our traditional assumptions, ultimately generating a scenario that forces participants to talk about the “unexpected” fallout from an event. This working challenge will be particularly relevant as they draw on the lessons from the response to the (or lack of coordinated) COVID-19 Pandemic.
The commercial, civil, and defense space sector has seen sweeping changes over the past decade that have more closely integrated space with the world economy. Emerging exponential technologies such as additive manufacturing, artificial intelligence, nanotechnology, digital automation, biotech and bioinformatics, robotics, and unmanned and autonomous systems, are highly relevant to the space enterprise but are increasingly developed by the broader technology sector. Solutions to the hardest problems facing government and society today will evolve from collaborative partnerships that combine talents and innovation.
The 5th Innovation Summit brings together luminaries from Federally Funded Research and Development Centers, University-Affiliated Research Centers, and Government-funded Laboratories to discuss innovative solutions to problems of national priority. The theme for the Summit is "Increased collaboration to address the rapidly changing landscape across the space enterprise, and the multi-domain operations it supports.” Within this collaboration theme, the Summit has tracks dedicated to:
- Earth Science Enterprise: The Role of Space Based Sensor Network addressing the “Unthinkable”
- Ensuring the Resilient Supply Chains: Essential Connections Between Talent and Technology
- Enabling Collaboration through Digital Engineering: Combining Models to Tackle Challenging Problems