FROM MODEL TO REASONING
My work intersects AI Reasoning, Language Modelling, Empirical Asset Pricing, and Autonomous System Design. I hold an MFE from Columbia Business School and HBSc in Computer Science from University of Toronto.
Currently, I am a lab member at Prof. Ronghui Gu's Lab at Columbia University Software System Lab, where I lead the OpenMath Initiatives.
VERIFIED INTELLIGENCE FOR INSTITUTIONAL FINANCE
Astra Indes
Bridging economic logic and mathematical verification—building systems where rigor, reasoning, and disciplined capital coexist, turning every model, forecast, and decision into provable intelligence.
At Astra Indes, we develop verified AI systems for institutional finance, ensuring that quantitative models are not just statistically sound but mathematically provable. Every forecast, every risk assessment, every trading decision is backed by formal verification—transforming intuition into rigorous, auditable intelligence.
astraindes.com →RESEARCH AREAS
AI Reasoning & Language Models
Advancing large language models for mathematical reasoning, formal verification, and structured problem-solving. Focus on bridging natural language understanding with finance theory and formal mathematical systems.
Empirical Asset Pricing
Applying machine learning and formal methods to understand cross-sectional return patterns, factor models, and market anomalies—building models that are both predictive and provably sound.
Autonomous & Reinforcement Learning Systems
Designing and implementing autonomous systems using reinforcement learning, with applications in algorithmic trading, statistical factor discovery, and multi-agent coordination with formal safety guarantees.
SELECTED PUBLICATIONS
Publications and preprints coming soon. Currently focused on OpenMath research at Columbia.