A meticulously curated collection of cutting-edge research, frameworks, and methodologies in Causal Artificial Intelligence.

Engineering-grade causal audit infrastructure for AI agents

Weighted doubly robust learning for uplift modeling

Official reproducibility experiments of the Thesis "Large Causal Models for Temporal Causal Discovery" at the University of Crete, Computer Science Department.

Causal inference methods for -omics research

Causal memory layer for AI agents. Prevents recurring failures by building a graph of action-outcome chains.

An enterprise-ready, Telegram-first AI platform for food vendors using ML, NLP, and real-time scheduling to dynamically optimize pricing and eliminate food waste.Architected with FastAPI, Next.js 15, and Supabase.

Causal credit risk engine

See what your code actually means. In 3D. Claude Opus 4.7 hackathon entry.

A simple way to visualize discrepancies between causal matrices of true and predicted directed acyclic graph

Eradicating integration debt via L3 Causal Digital Twins and a 'Team of Rivals' counterfactual simulation architecture. Stop reacting, start predicting.

My Master's dissertation, Large Causal Models for Temporal Causal Discovery.

PRD-AGI 2.0.2 – 14 causal AI applications for healthcare, finance, law, education, cybersecurity, mental health, and agriculture.

Fork of pgmpy, a Python library for probabilistic graphical models and causal AI.

Causal inference project using DoWhy to isolate the true marketing lift of bank contact methods. Applies Propensity Score Stratification to remove selection bias from raw campaign data and delivers an interactive ROI simulator for budget decision-making.