Lightcone Research
AI-assisted science with rigor at its core, building open-source infrastructure for reproducible, inspectable, and legible computational research.
At a Glance
- Academic Institutions
- Commercial R&D Labs
- Individual Scientific Researchers
AI Tools by Lightcone Research
(1)ASTRA
YAML Spec for Scientific Analysis
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Products & Services
An open-source specification and YAML schema for scientific research records that declares inputs, outputs, and methodological choices.
An open-source command-line toolchain that serves as an agentic execution layer for ASTRA, providing built-in provenance and materialized results.
Market Position
Positioned as a standard-setter for scientific rigor in the age of AI agents, providing a verifiable computational layer.
Leadership
Founders
François Lanusse
Senior CNRS researcher at the CosmoStat Laboratory. Lead at CNRS's AI for Science center. Background in deep learning, statistical modeling, and observational cosmology. Lead author of AstroCLIP and AION-1.
Liam Parker
Physics Ph.D. student at UC Berkeley and NSF Graduate Research Fellow. Researcher at BIDS focusing on cross-modal foundation models. Lead on AION-1 and AstroCLIP.
Executive Team
François Lanusse
Project Lead / CNRS Researcher
Cosmology and Machine Learning researcher at CNRS.
Liam Parker
Project Lead / UC Berkeley Researcher
Astrophysics and AI researcher at UC Berkeley.
Board of Directors
Founding Story
Founded by scientists at UC Berkeley and CNRS to bridge the gap between AI-driven scientific output and the rigor required for scientific vetting and reproduction.
Business Model
Revenue Model
Institutional/Grant-funded non-profit academic initiative supported by UC Berkeley and CNRS.
Pricing Tiers
All tools (ASTRA, CLI) are licensed under BSD-3-Clause for academic and commercial use.
Target Markets
- Academic Institutions
- Commercial R&D Labs
- Individual Scientific Researchers
- AI-assisted astronomical research
- Reproducible computational discovery
- Standardizing scientific agent outputs
- Large-scale astronomical data analysis
- UC Berkeley
- CNRS
- CEA
- University of Toronto