PeopleofSuperintelligence

Researcher

Sebastian Graf

Sebastian Graf is a programming-language researcher whose work spans compiler analysis and formal program verification. A KIT work on call-arity analysis appeared in 2017; he coauthored lambda-lifting research in 2019 and a GHC coverage checker in 2020. At KIT, he completed a doctorate on functional abstract interpretation in 2024 and coauthored a method for deriving static analyses from a generic interpreter. At Lean FRO, he developed logic for monadic Lean programs in February 2025 and ported Lean's verification-condition generator to SymM in July 2026; Lean also supports AI-authored mathematics. As of October 2026, he is a Research Software Engineer at Lean FRO.

Works
5
Citations
9
h-index
1

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. August 2017

    Call Arity vs. Demand Analysis

    In August 2017, he publishes Call Arity vs. Demand Analysis as a KIT research work.

  2. 2019

    Selective lambda lifting

    In 2019, he and Simon Peyton Jones publish an optimizing code-generation strategy for functional languages. It uses heuristics to select beneficial lambda lifts and estimates their effect on heap allocation in the Glasgow Haskell Compiler.

  3. August 2020

    Lower Your Guards

    In August 2020, he coauthors Lower Your Guards with Simon Peyton Jones and Ryan G. Scott, a compositional checker for Haskell pattern matches. The algorithm reduces complex patterns to guard trees and is implemented in GHC.

  4. 2024

    Abstracting Denotational Interpreters

    In 2024, he coauthors Abstracting Denotational Interpreters with Simon Peyton Jones and Sven Keidel. The generic interpreter yields dynamic semantics and summary-based static analyses, including type analysis.

  5. December 2024

    A KIT doctorate

    In December 2024, he completes a doctorate at KIT with a thesis titled Functional Abstract Interpretation. The thesis presents a more efficient and precise static analysis for Haskell pattern-match coverage and a design pattern for deriving higher-order analyses from a generic interpreter.

  6. February 2025

    Program logic for Lean monads

    In February 2025, he works on behalf of Lean FRO on a Floyd/Hoare-style program logic for verifying monadic code in Lean. It is designed to let users define monads and verify programs with shared logic and automation.

  7. July 2026

    Porting vcgen to SymM

    In July 2026, he ports Lean's verification-condition generator for monadic programs to SymM, a monadic framework for high-performance software verification. Lean also supports AI-authored mathematics, where AI agents write and review the code.

  8. As of October 2026

    Research Software Engineer

    As of October 2026, he is a Research Software Engineer at Lean FRO. He works on a verification condition generator for monadic programs written in Lean.

Career

  1. NowLean Focused Research OrganizationResearch Software Engineer

Education

  1. 2024Karlsruhe Institute of TechnologyDoctorate

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Lower your guards: a compositional pattern-match coverage checker2020 · Proceedings of the ACM on Programming Languages · 8 citations
  2. Triemaps that Match2025 · Lecture notes in computer science · 0 citations
  3. Two Independent and Highly Efficient Open Source TKF91 Implementations2015 · 0 citations

From OpenAlex, as of 21 October 2026.

  1. Google has the highest combined h-index among AI organizationsIncludes Convergent Research. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Karlsruhe Institute of Technology. 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.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Karlsruhe Institute of Technology. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes Karlsruhe Institute of Technology. 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.

Colleagues

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

Sources and credits

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  1. Other Publications: Call Arity vs. Demand Analysis pp.ipd.kit.edu. Checked 20 October 2026.
  2. Other Publications: Selective Lambda Lifting pp.ipd.kit.edu. Checked 20 October 2026.
  3. Journal Article: Lower Your Guards: A Compositional Pattern-Match Coverage Checker pp.ipd.kit.edu. Checked 20 October 2026.
  4. Abstracting Denotational Interpreters arxiv.org. Checked 20 October 2026.
  5. Ph.D. thesis: Functional Abstract Interpretation pp.ipd.kit.edu. Checked 20 October 2026.
  6. Monadic program logic: Request for feedback | Zulip Chat Archive leanprover-community.github.io. Checked 20 October 2026.
  7. The Lean Theorem Prover: Design, Evolution, and Impact leodemoura.github.io. Checked 20 October 2026.
  8. fixpt · About fixpt.de. Checked 20 October 2026.
  9. Team — Lean Lang lean-lang.org. Checked 20 October 2026.