Research
Publications
Research papers on orbital machine learning, tracking algorithms, and space computing infrastructure.
Published
Peer-distributed and preprint publications.
Constraint-Aware Execution Planning for Hybrid Space-Ground Compute Workloads
A planning system that produces feasible execution plans for hybrid space-ground compute workloads under power, thermal, communication, and compute constraints. Deployed in production as the CAE API.
Upcoming publications
Papers in preparation as our research matures. Follow our blog for early insights.
ML Approaches for Orbital Conjunction Analysis
Real-time Satellite Tracking at Scale
Active research areas
Our papers span these research tracks.
Orbital Machine Learning
ML models for orbital prediction, maneuver detection, and conjunction forecasting
- Orbit determination from sparse observations
- Maneuver detection and prediction
- Conjunction probability with uncertainty quantification
- Satellite behavior classification
Tracking Algorithms
High-performance algorithms for satellite tracking and TLE propagation
- SGP4/SDP4 optimization
- Multi-object tracking
- Sensor fusion for tracking
- Real-time catalog maintenance
Distributed Computing
ML for federated learning and workload distribution across Earth-space infrastructure
- Gradient compression for high-latency links
- Model partitioning for heterogeneous nodes
- Synchronization scheduling under intermittent connectivity
- Bandwidth prediction for inter-satellite links
Collaborate with us
We welcome academic collaborations, co-authored publications, and research partnerships.