Economic World Models Initiative

The Economic World Models Initiative develops next-generation AI-powered simulation systems for economies, markets, organisations, and societies. Economic World Models combine large environment models, agent-based systems, economic theory, data-driven learning, equilibrium reasoning, and institutional constraints to study how humans, firms, markets, policies, and AI agents interact under alternative scenarios. The Initiative aims to build foundations, platforms, and applications for market simulation, on-chain economies, financial infrastructure, policy experimentation, business decision-making, and risk analysis, helping researchers, policymakers, and industry leaders test complex economic systems before decisions are deployed in the real world.

• Faculty Leads: Lin William Cong and Dacheng Tao
• Faculty Co-Leads: Yang Liu and Benyou Wang
• Industry Co-Lead: Yunbo Lu

Global InferenceNet Initiative

The Global InferenceNet Initiative builds shared infrastructure for training, evaluating, and deploying AI agents in economics, finance, business, and the social sciences. It develops large-scale databases of empirical research tasks, econometric analyses, data-code workflows, and research designs, together with benchmarks and competitions that test whether AI agents can plan, execute, interpret, and audit professional-level analytical work. By combining research benchmarking, educational resources, textbooks, digital refereeing tools, and applied services for analysts and consultants, InferenceNet aims to improve productivity, reproducibility, and training for both human researchers and AI-powered economic and financial intelligence.

• Faculty Lead: Ye Luo
• Faculty Co-Leads: Lin William Cong and Dacheng Tao

Autonomous Innovation & Research (AIR) Initiative

AIR Initiative studies and builds AI systems that can support, accelerate, and partially automate research and innovation across science, engineering, business, social sciences, and the humanities. The Initiative develops workflows, platforms, and evaluation protocols for AI researchers, AI scientists, literature-discovery agents, hypothesis-generation systems, experiment-design tools, and human-AI collaboration in knowledge production. AIR aims to create new models of research productivity while preserving rigour, creativity, domain expertise, and human judgment in the discovery process.

• Faculty Lead: Yang Liu
• Faculty Co-Leads: Lin William Cong and Dacheng Tao

Intelligent Economy Initiative 

Explores how AI, autonomous systems, advanced computing, extended reality, and trusted digital infrastructure are transforming production, finance, commerce, and governance. Develops technologies, standards, and economic frameworks needed for a more innovative, resilient, sustainable, and socially beneficial economy.

• Faculty Lead: Will Cong and Luyao Zhang

Centre of AI for Social Science

The AI for Social Science (AI4S2) Centre advances research on how artificial intelligence can transform social science, business research, and policy analysis while remaining grounded in human behaviour, institutions, culture, and social context. The Centre develops AI methods for surveys, experiments, causal inference, organisational analysis, behavioural studies, economic reasoning, and human–machine interaction, while also studying the social behaviour, biases, reasoning, and alignment of AI agents themselves. AI4S2 aims to connect computer science with economics, finance, management, psychology, law, humanities, and public policy, creating new tools for understanding societies in the age of AI.

• Centre Director: Yohanes Eko Riyanto
• Centre Co-Director: Te Bao
• Advisory Director: Lin William Cong

Investment Intelligence and Innovation Lab (I³ Lab)

The Investment Intelligence and Innovation Lab (I³ Lab) conducts research on AI-driven trading, quant trading, quantimental investing, on-chain finance, robo-advising, autonomous financial agents, market simulation, financial infra for machines, family office/business digitisation, and other emerging technologies relevant for investment. Designed as an industry-facing research lab, I³ connects academic rigour with practical innovation to help shape the future of investment management and intelligent financial markets.

• Principal Investigator: TBA
• Co-Principal Investigator: Jianfeng Hu

Digital Economy and Financial Technology Lab (DEFT Lab)

Incubated through the FinTech Initiative at Cornell SC Johnson College of Business and Cornell Tech, DEFT Lab conducts research on digital payments, blockchain-based systems, decentralised finance, tokenomics, AI for finance, digital platforms, and the economics of emerging financial technologies. The Lab studies how new technologies reshape financial markets, firms, platforms, contracts, entrepreneurship, and economic organisation. By integrating financial economics, information economics, data science, and applied theory, DEFT provides rigorous insights for businesses, policymakers, investors, and innovators navigating the digital economy.

• Principal Investigator: Lin William Cong
• Co-Principal Investigator: Zhimin Chen