Machine Learning for Space
Space is becoming a crowded, data-rich, and safety-critical environment. My work in machine learning for space focuses on the tools needed to understand and operate in that environment: predicting orbits, estimating uncertainty, organizing resident space-object data, and building AI systems that support space-operations decisions.
The research spans physics-aware forecasting, orbit determination, diffusion models for uncertainty, language models and retrieval-augmented generation for operational knowledge, and reinforcement-learning benchmarks for orbital systems. A recurring theme is trust: models should be accurate, efficient, and useful to operators working under uncertainty.
Publications in this topic
- A Systematic Evaluation of Retrieval-Augmented Generation and Language Models for Space Operations, AI4Space, 2026.
- Generalizing Trilateration: Approximate Maximum Likelihood Estimator for Initial Orbit Determination in Low Earth Orbit, IEEE Transactions on Aerospace and Electronic Systems, 2025.
- OrbitZoo: Real Orbital Systems Challenges for Reinforcement Learning, NeurIPS, 2025.
- Language Modeling and Retrieval-Augmented Generation for Integration in Space Operation Decision Support Tools, IAA Symposium on Safety, Quality and Knowledge Management in Space Activities, 2025.
- Machine learning in orbit estimation: A survey, Acta Astronautica, 2024.
- Precise and Efficient Orbit Prediction in LEO with Machine Learning using Exogenous Variables, IEEE Congress on Evolutionary Computation, 2024.
- One-Shot Initial Orbit Determination in Low-Earth Orbit, IEEE Aerospace Conference, 2024.
- AI for space traffic management, Journal of Space Safety Engineering, 2023.
- Predicting the Position Uncertainty at the Time of Closest Approach with Diffusion Models, International Astronautical Congress, 2023.
- Taxonomy for Resident Space Objects in LEO, International Astronautical Congress, 2023.
- Conjunction Data Messages behave as a Poisson Process, Workshop on AI for Spacecraft Longevity, 2021.