Paper Accepted at ICGHIT 2026
International Conference Acceptance
Green & Sustainable Computing
Space-Based AI Infrastructure
ICGHIT Edition
Paper Accepted at ICGHIT 2026
My research paper "Orbital Intelligence: A Vision for Sustainable Large Language Model Training and Inference in Space" has been accepted at the 14th International Conference on Green and Human Information Technology (ICGHIT 2026). The paper proposes a novel vision for leveraging space-based infrastructure to make LLM training and inference more energy-efficient and sustainable.
Paper Abstract
As Large Language Models grow in scale, their energy and computational demands pose serious sustainability challenges. This paper presents Orbital Intelligence — a visionary framework for training and running LLMs aboard orbital platforms, exploiting abundant solar energy, natural cooling from space, and reduced latency for distributed inference. The work explores feasibility, architectural considerations, and the long-term potential of space as a sustainable compute environment for AI.
Research Focus
Sustainable AI at Scale – Exploring how orbital infrastructure can address the growing energy footprint of large language models.
- Solar Energy: Unlimited renewable power in orbit
- Passive Cooling: Space thermal environment for hardware
- Distributed Inference: Edge AI from orbital nodes
- Feasibility Analysis: Technical and economic considerations
About ICGHIT 2026
ICGHIT is an international conference focused on green and human-centered information technology. The 14th edition continues its mission of promoting sustainable innovation in computing and AI systems.
- Theme: Green & Human Information Technology
- Edition: 14th International Conference
- Focus: Sustainable computing, AI, and green IT
Key Concepts
Core ideas explored in the Orbital Intelligence framework.
- LLM Training in Orbit: Satellite-hosted GPU clusters
- Renewable Energy: Solar-powered compute nodes
- Thermal Management: Space-based cooling advantages
- Network Architecture: Low-latency orbital mesh
Impact & Contributions
Research contributions toward greener AI infrastructure.
- Vision Paper: Foundational framework for orbital AI
- Sustainability: Reducing terrestrial energy demands of LLMs
- Scalability: Orbital expansion pathways for AI compute
- Interdisciplinary: Bridging AI, aerospace, and green IT
The acceptance of this paper at ICGHIT 2026 marks an exciting step in bringing together two frontier fields — large language models and sustainable space infrastructure. As AI continues to grow in scale, rethinking where and how we compute is not just an engineering challenge, but a planetary responsibility.
This work reflects my commitment to research that is not only technically innovative but also mindful of its environmental and societal impact.