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Nobel Chemist Omar Yaghi Leaves Berkeley to Lead Tsinghua AI Lab

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TL;DR

  • Yaghi cited US grant cuts and American researchers' failure to adopt AI 'as a matter of survival' as the explicit reasons for his departure from Berkeley.
  • Roughly half of Yaghi's approximately 200 career mentees were Chinese nationals, giving Tsinghua a ready-made talent pipeline bundled into the hire.
  • Yaghi held an honorary professorship at Tsinghua since 2022, making the full appointment a formalization of an existing relationship rather than a cold recruitment.

A newly-minted Nobel laureate leaving Berkeley for Beijing is unusual on its own. The reason he gave is what makes it worth reading.

Omar Yaghi, who shared the 2025 Nobel Prize in Chemistry with Richard Robson and Susumu Kitagawa for metal-organic frameworks, has joined Tsinghua University to lead a new AI for Chemistry and Materials Science Research Center. The announcement landed on July 4, according to reporting from the South China Morning Post. Yaghi, 61, was previously the James and Neeltje Tretter professor of chemistry at UC Berkeley.

The stated research angle is a familiar AI-for-science pitch: use models to shorten materials design and synthesis cycles "by orders of magnitude," pointed at water scarcity, carbon neutrality, and sustainable development, the real-world jobs MOFs already do at lab scale (capturing carbon, harvesting water from desert air, absorbing hydrogen for clean energy). What is less familiar is the framing Yaghi gave alongside the move. In a Nature interview, he described the current state of US science as "not so encouraging because of the cutting back on grants," and said US researchers were not embracing what he sees as an "AI revolution," arguing engagement with AI models is "a matter of survival of the advanced research system in the US."

Why this matters beyond one appointment: a fresh laureate has publicly attached a talent move to US funding conditions and an AI-adoption gap, at a moment when Beijing is loudly recruiting. Yaghi trained approximately 200 researchers during his UC Berkeley tenure, nearly half of whom were Chinese, which gives the new Tsinghua center an alumni network to draw from immediately.

The honest caveat is that "orders of magnitude" is a hope, not a delivered result, and the reporting does not give you the terms of his appointment: full-time versus dual affiliation, funding scale, compute, what happens to his Berkeley group. Take those specifics as reported, not settled. The direction worth watching is whether more senior US-based principal investigators follow the same route, and whether this center starts producing real MOF designs against water and carbon in a timeframe short enough to matter.

What others are reporting

Coverage cluster as of 2h after publish

  1. Nature Read →

    Connects the move to Trump administration funding cuts, France's counter-recruitment push, and Yaghi's warning that US researchers must treat AI adoption as a survival imperative.

    The current state of US science is 'not so encouraging because of the cutting back on grants.'
  2. VnExpress International Read →

    Surfaces Yaghi's deep China ties: honorary Tsinghua status since 2022, roughly half of his 200 mentees Chinese, and the Yaghi Science Initiative now spanning seven countries.

    When doing research, he told us not to just think about the science itself or publishing papers, but also how to make our work known to the world.
  3. AcademicJobs Read →

    Academic labor-market read: examines downstream effects on Tsinghua graduate and postdoc pipelines and frames the hire within Asia's systematic rise as a top-researcher recruiting destination.

    The university-level institute will focus on AI-enabled technologies for materials design and synthesis.
  4. BigGo Finance Read →

    Frames the move within China's 'talent black hole' strategy of offering research autonomy over salary, and ties AI-materials integration directly to semiconductor and clean-energy geopolitics.

    AI materials chemistry is the future research paradigm for designing new materials in a faster, cheaper, and more sustainable way.