Research Areas
Explore our six core research domains advancing AI safety, governance, and autonomous systems safety globally.
Core Research Domains
Our twelve research labs operate across six interconnected domains, each advancing critical aspects of AI safety science.
Developing methods to ensure AI systems remain aligned with human values and objectives, including adversarial robustness, specification gaming prevention, and long-term alignment verification.
Key Researchers
- Dr. Sarah Chen - Adversarial Robustness
- Dr. Akiko Nakamura - Value Alignment
- Dr. James Rodriguez - Governance Integration
Recent Outputs
- Mechanistic Interpretability Framework (2025)
- Alignment Testing Protocols (2025)
- Mesa-Optimization Analysis (2025)
Designing comprehensive governance structures for AI systems including policy frameworks, regulatory compliance, international coordination, and institutional mechanisms for oversight.
Key Researchers
- Dr. James Rodriguez - Framework Design
- Dr. Akiko Nakamura - Policy Analysis
- Dr. Emily Thompson - International Coordination
Recent Outputs
- 7-Layer Governance Stack (2025)
- Framework Comparison Study (2025)
- DSRB Analysis Report (2025)
Advancing distributed governance through Byzantine fault-tolerant consensus mechanisms, enabling resilient decision-making structures that don't rely on single points of failure.
Key Researchers
- Dr. James Rodriguez - Lead Researcher
- Dr. Wei Liu - Cryptography
- Dr. Rajesh Kumar - Implementation
Recent Outputs
- Consensus in AI Governance (2026)
- 22/33 Mechanism Analysis (2025)
- Scalability Benchmarks (2025)
Examining unique ethical and governance challenges in defence AI systems, including accountability, civilian protection, and compliance with international humanitarian law.
Key Researchers
- Dr. Emily Thompson - Governance Ethics
- Dr. Sarah Chen - Safety Assurance
- Military Advisory Board
Recent Outputs
- Defence Compliance Matrix (2026)
- CMMC Integration Guide (2025)
- DSRB Framework Analysis (2025)
Researching safe autonomous decision-making in complex real-world environments, including trust building, transparency requirements, and continuous verification mechanisms.
Key Researchers
- Dr. Akiko Nakamura - Trust Frameworks
- Dr. David Lee - Verification
- Dr. Maria Park - Explainability
Recent Outputs
- Autonomous Systems Ethics (2025)
- Trust Building Framework (2025)
- Red Teaming Methodology (2025)
Building the next generation of AI safety researchers and practitioners through education, training programs, and international capacity building initiatives.
Key Researchers
- Dr. Maria Park - Education Strategy
- Dr. Rachel Zhang - Training Programs
- International Partners - Capacity Building
Recent Outputs
- AI Safety Curriculum (2025)
- Internship Programs - 40+ nations
- Research Mentorship Network
Research Impact Metrics
Research Collaboration Opportunities
Joint Research
Partner with our labs on co-authored papers, shared research agendas, and collaborative projects advancing AI safety science globally.
Contact Research Team →Internships & Postdocs
Competitive positions for graduate students and early-career researchers. Support for relocation, mentorship from leading researchers, and publication opportunities.
Apply Now →Research Funding
Grants and fellowships supporting research in AI safety, governance, and autonomous systems. Flexible funding models for diverse research approaches.
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