We’re excited to share highlights from a productive meeting with the Aviation Science Department at TU Delft, centered on the professor whose research and models inspired key elements of our intelligence capabilities.
The discussion reinforced how high-confidence prediction models can elevate decision support in aviation and airspace management—and how DoROAD can translate scholarly insights into deployable, mission-ready solutions.
What stood out in the conversation
- Translating theory into practice: The professor’s models provided a rigorous foundation for predictive reasoning. We explored how these concepts can be integrated with DoROAD’s real-world data to yield actionable intelligence with confidence.
- High-confidence decision support: Our team discussed calibrating predictions to support operators in aviation and airspace contexts, ensuring decisions are timely, auditable, and grounded in robust analytics.
- A collaborative pathway: We talked about building on TU Delft’s research with our own data assets, creating a feedback loop that enhances both academic understanding and field-ready capabilities.
How we’ve built on the collaboration
- Data-informed modeling: We’ve taken foundational research and augmented it with our diverse data streams, strengthening predictive accuracy and relevance to defense-relevant aviation scenarios.
- Practical AI for aviation and airspace: The work is driving the development of AI-enabled capabilities that improve situational awareness, risk assessment, and decision support for complex airspace environments.
- C-UAS applicability: Among other use cases, we showcased how these models can underpin C‑UAS workflows—supporting detection, assessment, and response with a focus on reliability and safety.
Why this matters for DoROAD and our customers
- A domain-relevant edge: Using academically grounded models gives us a credible, replicable basis for our intelligence elements, while tailoring them to real-world aviation and airspace challenges.
- Sovereign, secure deployment: Our approach remains fully compatible with high-security environments, ensuring governance, data protection, and export-control considerations are integral from the start.
- Accelerated roadmap: The collaboration opens pathways to pilots and demonstrations that translate research into measurable operational outcomes for defense and mobility operators.
Next steps and collaboration plan
- Joint workshops and pilots: We’ll continue exploring hands-on pilots that put the TU Delft models to work with DoROAD data in controlled aviation environments.
- Governance and data integration: We’ll align on data sharing, security, and compliance frameworks to support scalable deployments while maintaining rigorous oversight.
- Knowledge exchange and publications: We anticipate joint insights that can be shared with the broader community, advancing responsible AI in aviation and airspace applications.
- Scheduling the next collaboration milestone: We’re looking forward to formalizing the next phase of activities, including a concrete plan for demonstrations and evaluation criteria.
If your organization is exploring AI-enabled decision support for aviation, airspace management, or C-UAS, we’d welcome a discussion on how this collaboration approach could translate into practical outcomes for your programs. Our team is ready to tailor demonstrations and pilots to your airspace environments, governance requirements, and security posture.
