Int'l Workshop on AI & Mathematical Methods for Real‑world Impact

Machine learning and statistical modeling for real‑world data

Integrating AI, ABM, and Mathematical Tools for Advances in Mining and Geology

Mathematical modeling, simulation, and dynamical systems

Explainable, interpretable, and trustworthy AI

Optimization, control, and decision‑making under uncertainty

Artificial Intelligence and Probabilistic Modeling for Sports Betting

AI for health, environment, climate, and public policy

Spatio‑temporal modeling, forecasting, and geospatial analytics

AI and mathematical tools for resource‑limited or data‑scarce settings

Hybrid AI–mathematics approaches (physics‑informed ML, model‑driven ML, etc.)

Case studies demonstrating real‑world impact

Probabilistic modeling, Bayesian inference, and uncertainty quantification

Numerical methods and scientific computing for AI systems

Graph theory, network science, and graph‑based machine learning

AI‑Driven Enterprise Management Strategies in Low Income Countries

Reinforcement learning and sequential decision processes

Optimization algorithms for large‑scale or complex systems

AI for epidemiology, disease modeling, and public health surveillance

Mathematical foundations of deep learning and representation learning

Fairness, robustness, and bias mitigation in AI models

Data assimilation, sensor fusion, and real‑time prediction

AI for sustainable development, agriculture, and natural resource management

Multi‑agent systems, game theory, and collective intelligence

AI‑driven mathematical modeling for mobility, logistics, and smart cities

Computational social science and socio‑economic modeling

Verification, validation, and reliability of AI‑based mathematical models

Interdisciplinary applications combining AI, mathematics, and domain expertise