Our society focuses on the intersection of machine learning, computational methods, and economic theory. We welcome and support research in the following key tracks: 本协会专注于机器学习、计算方法与经济学理论的交叉领域。我们重点关注并支持以下核心方向的研究：
Deep learning applications for analyzing DSGE and heterogeneous agent models.深度学习在分析 DSGE 模型与异质性主体模型中的前沿应用。
High-dimensional inference, causal machine learning, and non-parametric estimation.高维推断、因果机器学习与非参数估计方法。
Algorithmic pricing, mechanism design, and automated market makers.算法定价、机制设计以及自动做市商 (AMM) 理论与应用。
Reinforcement Learning for policy design and agent-based modeling.利用强化学习进行最优政策设计以及基于主体的复杂系统建模。
Large Language Models (LLMs) for economic modeling, central bank communications and sentiment analysis.大语言模型 (LLMs) 在经济建模、央行沟通解读及市场情绪分析中的创新应用。