PeopleofSuperintelligence

Researcher

Yury G. Kudryashov

Yury G. Kudryashov is a mathematician and formalization lead whose work spans Lean, Mathlib, and AI theorem proving. He completed a PhD in dynamical systems through a co-tutorship involving Moscow State University, École Normale Supérieure de Lyon, and the Independent University of Moscow, then presented work on vector-field bifurcations at Cornell in 2018. His affiliations shifted from Toronto to Texas A&M in 2022 as his Lean work formalized a version of the divergence theorem; he coauthored work in AI theorem proving on Aristotle in 2025 and a paper formalizing Banach manifold flows in 2026. As of October 2026, he is a Formalization Lead at Harmonic and a Mathlib maintainer.

Now at
Harmonic
Badges

Timeline

  1. 2010–2011

    A PhD in dynamical systems

    He completes a PhD in dynamical systems through a co-tutorship program involving Moscow State University, École Normale Supérieure de Lyon, and the Independent University of Moscow in 2010 and 2011. His thesis examines attractors of generic and random dynamical systems and dynamical billiards.

  2. 2017–2018

    Teaching and presenting at Cornell

    He teaches applied functional analysis at Cornell in spring 2017, covering infinite-dimensional vector spaces, operators, Hilbert spaces, and the Hahn–Banach theorem. In September 2018, he presents a Cornell seminar on bifurcations of planar vector fields.

  3. 2022

    From Toronto to Texas A&M

    He is affiliated with the University of Toronto at Mississauga through July 2022 and Texas A&M University from August 2022. His Lean work formalizes a version of the divergence theorem and uses it to prove the Cauchy–Goursat theorem for some simple domains, extending complex analysis in Mathlib.

  4. 2025

    Aristotle at the IMO

    He coauthors the paper that introduces Aristotle, an AI system combining formal verification with informal reasoning and achieving gold-medal-equivalent performance on the 2025 International Mathematical Olympiad problems. The system pairs a Lean proof search system with informal reasoning and a dedicated geometry solver.

  5. February 2026

    Flows on Banach manifolds

    In February 2026, he coauthors a Lean formalization of the existence and uniqueness theorems for integral curves of vector fields on Banach manifolds. The work builds on Mathlib's differential and integral calculus and Banach manifold libraries.

  6. As of October 2026

    Formalization Lead at Harmonic

    As of October 2026, he is a Formalization Lead at Harmonic and a maintainer of Mathlib. He formalizes mathematics in Lean from 2019 onward.

Career

  1. NowHarmonicFormalization Lead
  2. Until 2022University of Toronto
  3. From 2022Texas A&M UniversityPostdoc

From the biography.

  1. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Toronto. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  2. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Toronto. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  3. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorateIncludes University of Toronto. 84% of people shaping AI with recorded undergraduate and doctoral schools changed institutions for their doctorate. Across 2,116 people with both an undergraduate degree and a doctorate recorded, we trace which undergraduate schools feed which doctoral programs, how often students stay at the same school, and how paths differ by birth-country region.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Toronto. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. Yury Kudryashov | pi.math.cornell.edu pi.math.cornell.edu. Checked 22 October 2026.
  2. MATH 6220 - Applied Functional Analysis | pi.math.cornell.edu pi.math.cornell.edu. Checked 22 October 2026.
  3. Dynamical Systems Seminar | pi.math.cornell.edu pi.math.cornell.edu. Checked 22 October 2026.
  4. Formalizing the Divergence Theorem and the Cauchy Integral Formula in Lean drops.dagstuhl.de. Checked 22 October 2026.
  5. [2510.01346] Aristotle: IMO-level Automated Theorem Proving arxiv.org. Checked 22 October 2026.
  6. [2602.13247] Integral Curves and Flows on Banach Manifolds in Lean arxiv.org. Checked 22 October 2026.
  7. Mathlib maintainers leanprover-community.github.io. Checked 22 October 2026.