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Research & Partnerships

Curated working papers, benchmarks, and open datasets on verified financial algorithms, formal methods for quant models, and macro linkages between compute cycles and capital flows.

Research Areas

Verified Financial Algorithms

Formal verification of trading algorithms and risk models

Sample Papers:

Formal Verification of High-Frequency Trading Systems

Provably Safe Risk Management Protocols

Formal Methods for Quant Models

Mathematical foundations for quantitative financial models

Sample Papers:

Type-Safe Financial Modeling

Verified Statistical Arbitrage Strategies

Macro Linkages & Compute Cycles

Understanding the relationship between compute infrastructure and capital flows

Sample Papers:

Compute-Capital Correlation Analysis

Infrastructure Investment Alpha Generation

Research Partnerships

Columbia Business School

Academic Partnership

Extending the Columbia tradition of fundamental investing to the computational age

Focus:

Emprical asset pricing, Macro finance

Columbia University Software Systems Laboratory

Technical Collaboration

Advancing formal verification and mathematical reasoning for AI systems

Focus:

Formal methods, computational logic

The Fields Institute, Centre for Mathematical AI

Mathematical Research

Exploring the mathematical foundations of verified intelligence

Focus:

AI For Mathematics, Mathematics of AI

RiskLab International

Mathematical Finance Research

Developing verified risk models and quantitative methods

Focus:

Financial algorithms verification, Conformal prediction

ADIA Lab

Strategic Capital Deployment

Aligning verified intelligence with practical capital deployment

Focus:

Applied AI, real-world implementation

Research Philosophy

We support open, verifiable, and reproducible research bridging academic discovery and practical capital deployment. Our collaborations explore the frontier between AI, finance, and formal methods — advancing reasoning systems, computational infrastructure, and algorithmic governance.

Open Research Initiative

We believe in the power of open, verifiable research to advance the field of verified AI in finance.

Our working papers, benchmarks, and datasets are made available to the research community to foster collaboration and accelerate progress in formal verification methods for financial systems.

Working Papers

Peer-reviewed research on verified financial algorithms and formal methods

Open Datasets

Curated datasets for reproducible research in verified AI and finance