Quant AI and trading AI skills for quant agents and AI trading agents: causal market analysis, investment research, trading strategy discovery, alpha discovery, backtesting, and validation with Abel.

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

Engineering-grade causal audit infrastructure for AI agents

CML (Causal Memory Layer) — a foundational memory layer for recording reasons, permissions, and responsibility behind actions, not just events or results. Enables systems in AI, fintech, security, and distributed computing to preserve meaning and causal accountability across time, independent of execution or transport.

Weighted doubly robust learning for uplift modeling

Causal inference methods for -omics research

Official reproducibility experiments of the Thesis "Large Causal Models for Temporal Causal Discovery" at the University of Crete, Computer Science Department. Defended at November 12th, 2025.

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

C-DAG: replayable causal audit traces for high-risk financial AI decisions.

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

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.

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

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

Alternative approaches to AI

My Master's dissertation, Large Causal Models for Temporal Causal Discovery. Defended at November 12th, 2025.

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

Causal reasoning engine for KETER-PRIME-KDIF the "why" layer of Agentic Symbiotic Systemic Intelligence.

CAK: typed semantic control layer for AI-agent behavior, learning, replay, governance, portability, and cost control.

Architect of the Large Graph Model (LGM). Implementing the Canonical Causal Ontology (0–25) into hardware to bridge the gap between deterministic logic and physical reality. Engineering the first physical substrate for entropy-free ASI.