Maximvs

My AI & ML interests focus on knowledge representation, neuro-symbolic reasoning, explainable AI, and interdisciplinary research datasets. I develop Quantum Metaphysics of Connectedness (QMC), an open research program exploring structural invariants, conceptual dependencies, paradox-based reasoning, and cross-domain patterns. My current work includes a structured corpus of 100 research studies (2025-2026) designed for LLM training, retrieval-augmented generation (RAG), semantic search, knowledge graphs, and AI-assisted scientific reasoning. I am particularly interested in how AI systems distinguish established evidence from hypotheses, recognize structural analogies, and maintain logical consistency across scientific domains.