Fields Medal duo a triumph for Chinese education, global collaboration

KUALA LUMPUR, 25 JULY 2026 —

Headline: Fields Medal duo a triumph for Chinese education, global collaboration Lead: That China has talent has long been well-recognised but that two home-grown elites were awarded the Fields Medal, seen as the Nobel Prize for mathematics, proves more than that. The success of Wang Hong and Deng Yu is a tribute to the multiplying benefits of education at home, learning abroad and collaboration across borders. In a world facing complex challenges, this is exactly the kind of intellectual synergy humanity needs more of. For the first time, China has produced two Fields laureates... Body: For the first time, China has produced two Fields laureates in a single year, becoming only the fifth country – after the United States, France, Britain and Russia – to do so.

American John Pardon and Jacob Tsimerman, a Russian-born Canadian, also won this year. The prize is awarded every four years to mathematicians under the age of 40.

The Chinese winners were shaped first by solid training in their home country before advancing through overseas education and research. It shows that strong foundations, disciplined learning and rigorous academic pursuit can create world-class talent that shines even brighter when exposed to broader intellectual traditions and international exchanges.

Having studied at Peking University, Massachusetts Institute of Technology (MIT) and Princeton University, Deng was honoured for work in partial differential equations and connecting fundamental laws of physics to equations describing the behaviour of gases and fluids.

Wang won for major advances in harmonic analysis and geometric measure theory, including her work on the three-dimensional Kakeya conjecture. She studied at Ecole Polytechnique and Paris-Sud University in France after graduation from Peking University and completed her doctorate at MIT. Source: South China Morning Post Published: 2026-07-24T22:45:05.000Z Region: OSINT Topic: Economy (AI-assisted rewrite, based on the original source)