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  <title><![CDATA[Anton Leykin Awarded AI for Math Fund Grant]]></title>
  <body><![CDATA[<p dir="ltr">School of Mathematics Professor<a href="https://research.gatech.edu/people/anton-leykin">&nbsp;<strong>Anton Leykin</strong></a> is part of a research team selected to receive support through the <a href="https://www.renaissancephilanthropy.org/initiatives/ai-for-math-fund">AI for Math Fund</a>, a new grant program created to accelerate the development of artificial intelligence (AI) and machine learning tools for mathematics.</p><p dir="ltr">“This grant gives me a foothold in a new world where AI can be used in a very concrete way,” says Leykin. “It’s an opportunity to move beyond the hype and develop tools that truly benefit mathematical research.”</p><p dir="ltr">With a total of $18 million in inaugural grants to 29 project teams, the AI for Math Fund backs initiatives that create open-source tools, expand high-quality datasets for AI training, and make advanced systems more accessible to mathematicians.&nbsp;The fund received 280 grant applications from researchers and mathematicians worldwide.&nbsp;</p><p dir="ltr"><strong>Building bridges</strong></p><p dir="ltr">Leykin’s global team includes researchers from the University of South Carolina, University of Warwick, and Cornell University. Their project,&nbsp;<strong>“</strong><a href="https://www.renaissancephilanthropy.org/bridging-proof-and-computation-a-verified-leanmacaulay2-interface"><strong>Bridging Proof and Computation: For a Verified Lean-Macaulay2 Interface</strong></a><strong>,”</strong> aims to connect two powerful systems: Lean, a platform for assisting and formalizing mathematical proofs, and Macaulay2, a computational algebra system widely used in research.</p><p dir="ltr">By developing a native interface —&nbsp;a built-in connection that allows the two systems to work together without external tools —&nbsp;and a Lean-based domain-specific language, the project will enable communication between these systems. This will allow Lean users to formulate tactics that involve sophisticated computation done by algorithms implemented in Macaulay2; in return, Macaulay2 users can formalize computer-assisted proofs via Lean with a little help from AI.</p><p dir="ltr">“This integration has the potential to transform how mathematicians work,” says Leykin. “It will not only connect Lean and Macaulay2 but also lay the groundwork for a general interface that could benefit other computer algebra systems in the future.”</p><p dir="ltr">His goal is to create a robust proof-assistance system where AI can help generate strategies and validate proofs, driving progress in areas that require both computational power and rigorous verification.</p><p dir="ltr"><strong>About the AI for Math Fund</strong></p><p>A joint initiative developed in partnership between<a href="https://renaissancephilanthropy.org/">&nbsp;Renaissance Philanthropy</a> and founding donor<a href="https://www.xtxmarkets.com/">&nbsp;XTX Markets</a>, the AI for Math Fund is one of the largest&nbsp;philanthropic commitments supporting the development of AI and machine learning tools to advance mathematics. Individual grants range up to $1 million for 24 months of work on open-source projects and research.</p>]]></body>
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      <value>2025-11-11T00:00:00-05:00</value>
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      <value><![CDATA[Leykin and his international team are developing an AI-powered interface to link proof verification and computational algebra, aiming to transform how mathematicians collaborate and solve complex problems.]]></value>
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      <value><![CDATA[<p>Leykin and his international team are developing an AI-powered interface to link proof verification and computational algebra, aiming to transform how mathematicians collaborate and solve complex problems.</p>]]></value>
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            <title><![CDATA[Anton Leykin]]></title>
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      <email><![CDATA[laura.smith@cos.gatech.edu]]></email>
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      <value><![CDATA[<p>Laura Segraves Smith, writer</p>]]></value>
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