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Yucheng Yang receives Research Network Grant from 1st UZH Leading House Asia Pacific Funding Call

For project on "Machine learning for better economic decisions"

Multilateral Research Takes Shape Across the Asia-Pacific

The University of Zurich (UZH) serves as the Leading House for Switzerland's bilateral science and technology cooperation with the Asia-Pacific region for 2025–2028. Mandated by the State Secretariat for Education, Research and Innovation (SERI), UZH supports international research collaborations through a range of competitive funding instruments open to researchers at Swiss higher education and public research institutions.

Forty interdisciplinary projects will receive funding, including 33 multilateral projects. The UZH-led initiatives presented below offer a glimpse of this diversity, spanning climate communication and ecosystem restoration to machine learning, travel medicine, culturally grounded AI, and digital mental health.

Among the selected research projects is one led by Prof. Yucheng Yang from our department.

Yucheng Yang_2024

Machine learning can help economists tackle complex challenges, from climate policy to trade disruptions, and this project builds an international research and training network to advance this mission.

Yucheng Yang
Assistant Professor of Finance

Machine learning for better economic decisions

Economic models are increasingly used to understand complex systems, from climate policy to global trade. But many of today’s challenges are difficult to analyze with conventional computational tools alone. Yucheng Yang from the Department of Finance is building an international research and training network that links UZH with partner hubs in Hong Kong, Japan and China, including the University of Hong Kong, the National Graduate Institute for Policy Studies in Japan and Peking University.

The project brings together expertise in economics, finance, computer science and policy. It will explore how machine learning methods such as reinforcement learning and Bayesian optimization can be combined with economic theory in ways that remain interpretable, reproducible and useful for decision-making.

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