AI now produces results faster than the venues that check them.

Mathematics & AI is an open-access, peer-reviewed journal at the intersection of mathematics and artificial intelligence. The journal publishes original research in mathematical foundations of AI, machine learning theory, optimization, statistical learning, neural network analysis, computational mathematics, and AI-driven mathematical discovery.

Finance & AI is an open-access, peer-reviewed journal exploring the intersection of financial science and artificial intelligence. The journal publishes original research on machine learning for financial modeling, NLP for market analysis, algorithmic trading, AI-driven risk management, explainable AI in finance, blockchain and DeFi, quantitative methods, and regulatory technology.

Bioinformatics & AI bridges the gap between life sciences and intelligent computation. As biological datasets grow exponentially — from whole-genome sequencing to single-cell transcriptomics — AI methods become essential for extracting knowledge from complexity. The journal publishes original research on machine learning for genomics, protein structure prediction, drug discovery, medical imaging, and AI-driven analysis of biological data. Scope includes: Deep learning for genomics, proteomics, and metabolomics AI-assisted drug discovery and molecular design Protein structure and function prediction Medical image analysis and computational pathology NLP for biomedical literature Graph neural networks for molecular and biological networks Foundation models for biological sequences Explainable AI in healthcare and diagnostics Federated learning and privacy-preserving methods in biomedicine AI for epidemiology and public health modeling All submissions undergo rigorous double-blind peer review. Published articles receive a Crossref DOI and are immediately available under open access.

Autonomous AI Agents is a peer-reviewed, open-access journal for research on autonomous and agentic AI systems — their design, verification, safety, coordination, and governance. Scope: LLM-based agents and multi-agent systems; planning, tool-use, and autonomy; formal verification and trustworthy, accountable agent behavior; evaluation and benchmarking; agent infrastructure; and the societal, ethical, and policy dimensions of autonomous AI. Published by the International AI Committee (IAIC).